BMR (Mifflin-St Jeor) Calculator
The formula
Why Mifflin-St Jeor
Published in 1990 and validated repeatedly since, the Mifflin-St Jeor equation is the most accurate general-population BMR estimator — the Academy of Nutrition and Dietetics recommends it over the older Harris-Benedict, which systematically overestimates by about 5%. BMR covers roughly 60–70% of your total daily energy expenditure: the energy for breathing, circulation, cell repair and brain function at complete rest.
From BMR to daily calories
Multiply BMR by an activity factor to get TDEE (total daily energy expenditure): sedentary ×1.2, light ×1.375, moderate ×1.55, active ×1.725, athlete ×1.9. Our Calorie Needs Calculator does this for you.
Frequently asked questions
How accurate is this estimate?
Does BMR decline with age?
Source & methodology
Mifflin MD, St Jeor ST, et al. "A new predictive equation for resting energy expenditure in healthy individuals." Am J Clin Nutr. 1990;51(2):241-247.
BMR (Mifflin-St Jeor): the number, the method and the caveats
This page was written for one job: turning your own inputs into a defensible figure, with the working shown. There are plenty of pages about BMR (Mifflin-St Jeor); almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
In plain terms, BMR (Mifflin-St Jeor) answers the question "Your BMR (Mifflin-St Jeor)?". The measurement matters because it converts a situation that feels complicated — several inputs pulling in different directions — into a single number you can act on. Within Health & Medical, Nutrition is the context where this figure is quoted most often, and professionals treat it as a first-pass screen rather than a verdict.
Health figures in Health & Medical describe populations, not individuals — BMR (Mifflin-St Jeor) places you on a distribution built from bodies like yours, and the 1,758 kcal/day answer is a starting point for a conversation, not a diagnosis. That framing is the difference between using a health metric and being misled by one.
Every figure in the prose is generated by the engine rather than written beside it — the worked example resolves to BMR (Mifflin-St Jeor) = 1,758 kcal/day on the default inputs, and the sensitivity section ranks the inputs that move the result — Height first, at ≈6.3 % of the headline for a ten-percent error either way in that input. Work down the page and by the end you could re-derive the result in a spreadsheet from memory.
Inside the BMR (Mifflin-St Jeor) calculation: formula and every input
Here is the complete model this tool runs — BMR = 10·weight(kg) + 6.25·height(cm) − 5·age + 5 (men) / − 161 (women) — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
Sex (example value Male) is a branching choice rather than a figure you measure; the per-option effects are computed below. Replace the example with the figure from your own records — the tool recomputes instantly and the printed steps follow your numbers.
Age (years) (example value 32) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Use the value as of today, not as of the last time you looked — time fields drift silently.
Height (feet) (example value 5) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. Small measurement errors grow here: a length that is squared or cubed in the model magnifies a one-percent slip into a three-percent answer.
Height (inches) (example value 10) is a quantity rather than a category — precision here is cheap and worth having. Small measurement errors grow here: a length that is squared or cubed in the model magnifies a one-percent slip into a three-percent answer.
Height (cm) (example value 178) is a plain measured quantity — the unit shown in the label is the unit the formula expects. Small measurement errors grow here: a length that is squared or cubed in the model magnifies a one-percent slip into a three-percent answer.
Weight (lb) (example value 176) is a measured number in the unit named by the label; the formula does not convert for you. Stay in one unit system top to bottom; conversion rounding is where small errors enter.
Weight (kg) (example value 80) is a measured number in the unit named by the label; the formula does not convert for you. Weigh rather than estimate where you can — this field usually enters the formula multiplicatively.
What each “Sex” choice actually does: Male → 1,758 kcal/day · Female → 1,592 kcal/day These figures are computed from this engine, not estimated — switch the dropdown above and you will land on exactly these numbers.
BMR (Mifflin-St Jeor) with real numbers, step by step
Rather than describe the calculation, here it is end to end — every substitution in order, starting from the inputs above. Starting figures: Sex, Age (years), Height (feet), Height (inches). The computed BMR (Mifflin-St Jeor) comes out at 1,758 kcal/day, which the interpretation band labels “within the normal band”.
- Inputs: 80.0 kg, 178.0 cm, 32 years, male
- BMR = 10×80.0 + 6.25×178.0 − 5×32 + 5
- = 800 + 1113 − 160 + 5 = 1758 kcal/day
BMR per hour — 73.2 kcal. Compare it against the main result of 1,758 kcal/day before drawing conclusions.
BMR per kg of body weight — 22.0 kcal/kg/day. Read next to the headline, this is the figure that shows the shape of the trade-off.
Harris-Benedict (revised) for comparison — 1,833 kcal/day. Read next to the headline, this is the figure that shows the shape of the trade-off.
Difference between equations — 75 kcal. If your inputs change, this is usually the first companion figure to move.
Overwrite any input above and every line of this example updates with it — the substitution is live, not a screenshot of somebody else’s numbers.
Scenario table: BMR (Mifflin-St Jeor) at ±10 % and ±20 % of the key input
Single-point answers invite false confidence, so the same engine was run across a band around the input that matters most here. Each row is a full recalculation of BMR (Mifflin-St Jeor), not an interpolation.
| Height setting | Your BMR (Mifflin-St Jeor) |
|---|---|
| 80 % of the example value | 1,535 kcal/day |
| 90 % of the example value | 1,646 kcal/day |
| example inputs | 1,758 kcal/day |
| 110 % of the example value | 1,869 kcal/day |
| 120 % of the example value | 1,980 kcal/day |
That spread — 1,535 kcal/day at the low end, 1,980 kcal/day at the high — is what a careful read of BMR (Mifflin-St Jeor) looks like: a band you can state out loud, with the reason for each edge. Reproduce it in the form above by editing Height alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change BMR (Mifflin-St Jeor) the most
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the BMR (Mifflin-St Jeor). It is the fastest honest answer to “what matters most in BMR (Mifflin-St Jeor)?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Nudge Height by ±10 % and BMR (Mifflin-St Jeor) lands between 1,646 kcal/day and 1,869 kcal/day (sensitivity ≈6.3 %)
- Weight +10 % → BMR (Mifflin-St Jeor) = 1,838 kcal/day · −10 % → 1,678 kcal/day (the BMR (Mifflin-St Jeor) shifts ≈4.6 %)
- Nudge Age by ±10 % and BMR (Mifflin-St Jeor) lands between 1,742 kcal/day and 1,774 kcal/day (sensitivity ≈0.9 %)
Height is the dominant lever here: ten percent either way moves the result by about 6.3 %, from 1,646 kcal/day to 1,869 kcal/day. Spend your verification effort there first, and treat Weight as the second priority (≈4.6 % per ten percent). The remaining fields can sit at safe defaults without materially changing the answer — knowing which is which is what separates a careful calculation from an anxious one.
Is your BMR (Mifflin-St Jeor) good — reading the result bands
Nobody acts on a bare figure — they act on a figure with a comparison attached. The default case lands in the “within the normal band” band, and bands are deliberately wide because real situations overlap. How much of that band is luck? On Height alone ten percent either way covers 1,646 kcal/day to 1,869 kcal/day. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
The comparison worth making is not with somebody else’s BMR (Mifflin-St Jeor) but with the version of your own situation measured last quarter — same formula, same conventions, different inputs.
Why BMR (Mifflin-St Jeor) results go wrong — and how to prevent it
Reporting the headline and quietly discarding BMR per hour. The companions are where the shape of the trade-off survives the rounding.
Reporting the headline and quietly discarding BMR per hour. The companions are where the shape of the trade-off survives the rounding.
Attention is also misallocated between fields. Having measured this engine, we can say where it belongs: Height first, everything else second.
Another is comparing across contexts: a BMR (Mifflin-St Jeor) computed with one set of conventions should never be lined up against a figure computed with another. Check the inputs behind both before ranking them.
BMR (Mifflin-St Jeor) verification checklist
- State, in one sentence, which convention each rate, unit or period in the form is using.
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Put Height under a magnifier; the sensitivity table above is the reason why.
- Recompute once with the dominant input deliberately set low, and see whether the decision changes.
- Compare the output against one published benchmark or a colleague’s independent estimate.
- Repeat the ±10 % test on the inputs that matter and see whether the decision — not just the number — still holds.
Five steps from raw inputs to a figure you can defend
Using a calculator well sounds trivial, but the difference between a decision-grade figure and a throwaway one lives entirely in the routine. The routine for BMR (Mifflin-St Jeor) takes a minute to learn and applies to every input above.
Step 1 — start from evidence. The inputs behind BMR (Mifflin-St Jeor) are sex, age (years), height (feet), height (inches), height (cm), weight (lb) and the remaining fields listed above. Write them down with their source next to each one; if you cannot name where a figure came from, that is the input most likely to be wrong. Rounding early is the quietest way to introduce a permanent error.
Step 2 — start from the case you can defend. Enter pessimistic-but-honest figures first; the optimistic run is a ceiling, not a plan. A conclusion that holds on conservative inputs holds everywhere. A calculation you cannot explain to somebody else is a calculation you cannot defend.
Step 3 — isolate your variables. Change one field, observe, revert. The live sensitivity list does the ranking for the default inputs; verify it against your own, because dominance shifts when the starting point shifts. Suspiciously tidy answers deserve the same scrutiny as untidy ones.
Step 4 — stress before you commit. A decision that survives a ten-percent squeeze on its two biggest inputs needs no luck to be sound. One that does not survive is a decision about hope, not about arithmetic. Write the figure down before moving on; memory flatters whichever number you saw last.
Step 5 — record the context, not just the number. Note today’s date and the inputs alongside the 1,758 kcal/day output. Six months from now the context is what turns this figure into a trend. One decimal place more than your data supports is one decimal place of fiction.
From calculation to decision: where BMR (Mifflin-St Jeor) earns its keep
Numbers earn their keep in conversations, and BMR (Mifflin-St Jeor) is no exception. In Health & Medical discussions around Nutrition, this figure decides whether an option stays on the table: it converts an opinionated debate into an arithmetic one, and arithmetic is the only referee both sides accept. Suspiciously tidy answers deserve the same scrutiny as untidy ones.
The companion outputs — BMR per hour and BMR per kg of body weight — exist for the second stage of that screen: the headline sizes the prize, while the companions describe the trade-off you are accepting to get it. Comparisons are cheap: run the identical calculation for the alternative and look at the gap.
Treat BMR (Mifflin-St Jeor) like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. Estimates improve most when the worst case is written down in ink.
People also ask about BMR (Mifflin-St Jeor)
What affects BMR (Mifflin-St Jeor) the most?
Measured on this engine, Height is the dominant lever: moving it ±10 % shifts the BMR (Mifflin-St Jeor) across 1,646 kcal/day to 1,869 kcal/day — about 6.3 % of the headline, with Weight next at ≈4.6 %. The ranked list in the sensitivity section is computed live, not asserted from a template.
Which matters more: weight or height?
For BMR (Mifflin-St Jeor), Height wins the head-to-head (≈6.3 % against ≈4.6 % per ten-percent change). Knowing which input dominates is the difference between careful work and merely slow work.
How much does the “Sex” choice change the answer?
Across every option this tool offers, the BMR (Mifflin-St Jeor) ranges from 1,592 kcal/day (Female) to 1,758 kcal/day (Male) with all other inputs held at their example values. The per-option table is printed in the inputs section — this is a decision that genuinely moves the number, not a cosmetic dropdown.
What is a typical BMR (Mifflin-St Jeor)?
On the worked example above BMR (Mifflin-St Jeor) comes out at 1,758 kcal/day. Treat that as one point on a distribution rather than a norm: the bands, the companion outputs and the sensitivity ranking tell you how wide the plausible range really is.
How do I calculate BMR (Mifflin-St Jeor) by hand?
Use the stated model — BMR = 10·weight(kg) + 6.25·height(cm) − 5·age + 5 (men) / − 161 (women) — and substitute in the order the tool prints (it starts from Inputs: 80.0 kg, 178.0 cm, 32 years, male). On the example inputs the hand route lands on 1,758 kcal/day, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to BMR (Mifflin-St Jeor) if height changes by 10 %?
Try it in the form above and the printed substitution will follow you; the pre-computed answer for the defaults is 1,646 kcal/day to 1,869 kcal/day across the ten-percent probe, i.e. ≈6.3 % sensitivity on the BMR (Mifflin-St Jeor).
Is the BMR (Mifflin-St Jeor) result of 1,758 kcal/day good or bad?
Neither, on its own — the label “within the normal band” is the band this figure falls in for the example inputs, and your own inputs will place you elsewhere on the same ladder. Judge the number against your history and your alternatives, and remember that a ten-percent error in Height alone moves it by ≈6.3 %.
Does BMR (Mifflin-St Jeor) change with age?
Yes — reference bands shift deliberately across the lifespan, which is why this tool prints an interpretation rather than a bare number. Re-read the bands each time inputs like Sex change materially.
Can BMR (Mifflin-St Jeor) be negative or empty?
Yes, and that is informative rather than broken: a negative BMR (Mifflin-St Jeor) usually means the inputs encode an outflow or a shortfall, and the verdict band above labels exactly that situation instead of hiding it.
How accurate is this estimate?
Within roughly ±10% for most healthy adults. Individual variation is real — genetics, thyroid function, and body composition all shift actual BMR. Indirect calorimetry is the only precise measurement.
Does BMR decline with age?
Yes, about 1–2% per decade after 20, driven mostly by muscle loss and hormonal change. Resistance training and adequate protein meaningfully slow the decline.
Is my data private on this page?
Yes — computation happens locally in your browser, with no account, no tracking of your inputs and nothing sent to a server. The printed formula is the whole story of what happens to your figures.
What the labels on this page mean
- BMR per hour
- 73.2 kcal for the BMR (Mifflin-St Jeor) worked case; it sits next to the main result because it carries context the headline leaves out.
- BMR per kg of body weight
- 22.0 kcal/kg/day on the example inputs — a companion figure printed beside the headline of BMR (Mifflin-St Jeor) so that no result is read in isolation.
- Harris-Benedict (revised) for comparison
- 1,833 kcal/day on the example inputs — a companion figure printed beside the headline of BMR (Mifflin-St Jeor) so that no result is read in isolation.
- Your BMR (Mifflin-St Jeor)
- The primary output of this tool: 1,758 kcal/day for the default inputs, computed exactly from BMR = 10·weight(kg) + 6.25·height(cm) − 5·age + 5 (men) / − 161 (women).
- Worked example
- The calculation written out in full so that nothing on this page has to be taken on trust.
- Verdict band
- The plain-language label — here “within the normal band” — mapping the computed figure onto experience-based ranges for Health & Medical.
- Sensitivity (±10 %)
- How far the BMR (Mifflin-St Jeor) moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
Where the BMR (Mifflin-St Jeor) model comes from
The model is published arithmetic implemented exactly as written: BMR = 10·weight(kg) + 6.25·height(cm) − 5·age + 5 (men) / − 161 (women). Source of record: Mifflin MD, St Jeor ST, et al. "A new predictive equation for resting energy expenditure in healthy individuals." Am J Clin Nutr. 1990;51(2):241-247. Where a professional version of this calculation differs, it differs in inputs and jurisdiction-specific coefficients, not in the algebra — which is why re-checking your inputs beats hunting for a second calculator.
Nothing here replaces a qualified professional, and nothing here is approximate either — the arithmetic is exact, and the honesty is in the inputs you supply. What that buys you is reproducibility — two people, two browsers, the same arithmetic, and a printed trail from inputs to result that either of them can audit.
What to do with your BMR (Mifflin-St Jeor) next
Re-run the calculation with your own figures, stress the two most sensitive inputs by ±10 %, and only then act on the result.
Whoever you are (people who need one trustworthy number before their next decision), the next step is the same: replace the example inputs with your own, note the date, and re-run whenever a figure moves. In Health & Medical, a dated figure is a trend, and an undated one is a rumour.