Mifflin-St Jeor is the BMR equation with the best validation record, which is why our calculator uses it — but "best" here means "wrong by the smallest amount for the most people", not "right for you". Harris-Benedict runs about 5% high against modern measurements, and the lean-mass equations (Cunningham, Katch-McArdle) are only as good as the body-fat number you feed them. Here is how the four compare, with the receipts.

The four equations side by side

EquationYear · sampleInputsFormula (kcal/day)
Mifflin-St Jeor11990 · 498 adults, 19–78 yweight, height, age, sexmen 10w + 6.25h − 5a + 5 · women 10w + 6.25h − 5a − 161
Harris-Benedict21918 · 136 men, 103 womenweight, height, age, sexmen 66.4730 + 13.7516w + 5.0033h − 6.7550a · women 655.0955 + 9.5634w + 1.8496h − 4.6756a
Cunningham31980 · 223 subjects (re-analysis of the Harris-Benedict data)lean body mass500 + 22 × LBM
Katch-McArdletextbook equation (McArdle, Katch & Katch, *Exercise Physiology*)lean body masssame family as Cunningham — a constant plus a coefficient on lean mass; we have not verified the printed coefficients against the book, so they are not reproduced here

w = weight in kg, h = height in cm, a = age in years, LBM = lean body mass in kg.

Two families, then. Mifflin-St Jeor and Harris-Benedict describe you by size, age and sex. Cunningham and Katch-McArdle describe you by how much non-fat tissue you carry, which is the tissue that actually spends most of the resting energy — Cunningham's re-analysis found lean body mass to be the single predictor of BMR, with sex and age adding little once it was known3.

What each one needs as input

  • Weight, height, age, sex — everyone has these. They are what Mifflin-St Jeor and Harris-Benedict need, and they are why those two are the default in almost every calculator, including ours.
  • Lean body mass — you need a body-fat percentage to get it: LBM = weight × (1 − body fat). A skinfold, a DEXA scan or a bioimpedance scale gives a number; a guess gives a guess.

The trade-off is exact. The lean-mass equations skip the population averages for sex and age, but they import whatever error is in your body-fat figure. Five percentage points of body-fat error on an 85 kg person is 4.25 kg of lean mass, which in Cunningham's equation is 22 × 4.25 ≈ 94 kcal of BMR. Most people's body-fat estimate is off by more than five points.

How wrong they typically are

For our standard example — man, 30 years, 180 cm, 85 kg:

EquationBMR (kcal/day)Note
Mifflin-St Jeor1,830our calculator's value
Harris-Benedict1,93366.4730 + 13.7516×85 + 5.0033×180 − 6.7550×30
Cunningham at 15% body fat2,090LBM = 72.25500 + 22 × 72.25
Cunningham at 25% body fat1,903LBM = 63.75500 + 22 × 63.75

Harris-Benedict lands 103 kcal above Mifflin-St Jeor here — 5.6% — which matches what Mifflin and colleagues found across their whole sample: the 1918 equations overestimated measured resting expenditure by 5%1. Cunningham swings by 187 kcal between two plausible body-fat guesses for the same man, which is the lean-mass trade-off in one row.

Against measurement rather than against each other, the picture is humbler still. Mifflin-St Jeor explains 71% of the variance in measured resting expenditure in its own development sample1. The 2005 systematic review by Frankenfield and colleagues, which pooled validation studies reporting individual errors, concluded that Mifflin-St Jeor was the most reliable of the four equations in common clinical use — predicting resting metabolic rate within 10% of measured in more non-obese and obese adults than Harris-Benedict, Owen or WHO/FAO/UNU, with the narrowest error range — and in the same breath that noteworthy errors and limitations exist when it is applied to individuals4.

Put a number on "within 10%": for a 1,830 kcal BMR that is a ±183 kcal band, and "most people" inside the band means a meaningful minority outside it. As a working rule, a population equation is typically 100–200 kcal off for an individual, and 400–500 kcal misses are not rare. This is why we describe every calculator output as a starting estimate and why the app's expenditure model replaces it with your own data as soon as there is enough of it.

In plain terms: the equations differ from each other by about a hundred kcal; each of them can differ from you by several hundred.

Why we use Mifflin-St Jeor

Three reasons, in order:

  1. It has the best validation record. The Frankenfield review is the most systematic head-to-head we have, and it favours Mifflin-St Jeor on both the share of people within 10% and the width of the error range4.
  2. It needs only what everyone knows. Sex, age, height, weight. A calculator that asks for body fat gets a guess back from most users, and a lean-mass equation fed a guess is not more accurate — it is differently wrong.
  3. It was fitted on people like the people who use calculators. Mifflin's sample was half women and half people with obesity, aged 19–781; the Harris-Benedict sample was 239 mostly young, mostly lean adults measured a century ago2.

None of that makes it correct for you. It makes it the least-bad first guess, which is all a first guess has to be.

This is a comparison of population formulas, not medical advice. The differences between equations are smaller than the difference between any equation and a given person — which is why two weeks of logged intake and trend weight beats all four.

The short version

Four equations, two families: Mifflin-St Jeor and Harris-Benedict from size, age and sex; Cunningham and Katch-McArdle from lean mass. For our 85 kg example they land between 1,830 and 2,090 kcal. Mifflin-St Jeor has the best validation record and needs no body-fat guess, so it is our default — and it is still typically 100–200 kcal off for any one person. Educational overview only — not medical advice.