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Ideal Body Weight Calculator

Compare ideal body weight across Devine, Robinson, Miller, and Hamwi medical formulas

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Informational & Educational Physiology Calculator: All calculations provided are mathematical estimates derived from standard population equations (WHO, Asian-Pacific Consensus, US Navy, Devine, etc.). They are designed for general personal reference and do not constitute clinical diagnosis, medical evaluations, or individualized nutritional therapy. Consult a licensed medical doctor or dietitian before making major health changes.

Physical Parametersmetric

cm
kg
Consensus Ideal Body Weight
70kg0 kg from current
Devine (1974)
70.5 kg
Robinson (1983)
68.9 kg
Miller (1983)
68.7 kg
Hamwi (1964)
72 kg
Normal WHO Weight Window (BMI 18.5 – 24.9)
56.7 – 76.3 kg

Broadest epidemiological range associated with lowest long-term all-cause mortality rates.

About Ideal Body Weight Calculator

Compare ideal body weight (IBW) across the four recognized clinical formulas: Devine (1974), Robinson (1983), Miller (1983), and Hamwi (1964). Includes healthy WHO BMI (18.5 – 24.9) weight boundaries and consensus average.

Key Capabilities & Features

  • Four clinical medical equations: Devine (1974), Robinson (1983), Miller (1983), and Hamwi (1964)
  • Consensus average calculation combining all 4 clinical models
  • Epidemiological WHO normal BMI (18.5 – 24.9) window comparison
  • Dual metric (kg) and imperial (lbs) live toggles

How to Use Ideal Body Weight Calculator

1

Select Biological Sex

Choose male or female for formula constants.

2

Enter Height

Input height in cm or feet and inches.

3

Compare Formulas

Inspect side-by-side results from Devine, Robinson, Miller, and Hamwi models.

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Frequently Asked Questions

Why was the Devine formula created?

The Devine formula was originally developed in 1974 by Dr. Ben J. Devine to estimate medicinal drug dosages (e.g. theophylline) in clinical pharmacokinetics.

Which ideal weight formula is the most accurate?

The Robinson and Miller formulas updated Devine with empirical population revisions, but reviewing the consensus average provides the most balanced perspective.