OBJECTIVE: Insulin resistance and impaired beta-cell function are key elements in the pathogenesis of type 2 diabetes. We aimed to develop valid algorithms for estimation of the insulin sensitivity index (S(I)) and acute insulin response (AIR) derived from simple and cheap physiological measurements that could be used in large-scale metabolic, genetic, and epidemiological studies. RESEARCH DESIGN AND METHODS: For our purpose, data from an oral glucose tolerance test (OGTT) (18 samples during 240 min) and a tolbutamide-modified intravenous glucose tolerance test (IVGTT) (33 samples during 180 min) from 258 individuals with fasting plasma glucose <7 mmol/l and 2-h plasma glucose <7.8 mmol/l were used for model development and internal validation. Data from an additional 28 individuals were used for external validation. Bergman's minimal model was used to calculate S(I), and the trapezoidal method was used to calculate AIR(0-8 min). Multiple linear regression was applied to derive predictive equations of log(S(I)) and log(AIR(0-8 min)) using data on sex, BMI, plasma glucose, and serum insulin levels obtained during the OGTT. RESULTS: We demonstrate that it is possible to obtain estimates of S(I) (BIGTT-S(I)) and AIR (BIGTT-AIR) that are highly correlated to IVGTT-derived values of S(I) (R(2) = 0.77) and AIR (R(2) = 0.54). In the two validation datasets we obtained similar results. CONCLUSIONS: Data from OGTTs can provide accurate measures of insulin sensitivity and beta-cell function, which can be used in large scale metabolic, genetic, and epidemiological studies.