BACKGROUND: The standard method of identifying persons at high risk for type 2 diabetes mellitus involves detection of impaired glucose tolerance, which requires a costly and inconvenient 2-hour oral glucose tolerance test. Because clinical trials have indicated that diabetes is preventable by using behavioral or pharmacologic interventions, less expensive methods of identifying high-risk persons are needed. OBJECTIVE: To determine whether multivariable models are superior to glucose tolerance tests for identifying persons at high risk for diabetes mellitus. DESIGN: Prospective cohort study. SETTING: San Antonio, Texas. PARTICIPANTS: 1791 Mexican Americans and 1112 non-Hispanic whites without diabetes at baseline who were randomly selected from census tracts. MEASUREMENTS: Medical history; body mass index; blood pressure; fasting and 2-hour plasma glucose levels; fasting serum total, low-density lipoprotein, and high-density lipoprotein cholesterol levels; and triglyceride level. RESULTS: For prediction of 7.5-year incidence of type 2 diabetes, the area under the receiver-operating characteristic (ROC) curve for a multivariable model involving readily available clinical variables was significantly (P < 0.001) greater than the area under the ROC curve for the 2-hour glucose value alone (84.3% vs. 77.5%). Impaired glucose tolerance represents a single point on the latter curve. Adding the 2-hour glucose measurement to the multivariable model increased the area under its ROC curve, but only from 84.3% to 85.7%. CONCLUSION: Persons at high risk for diabetes mellitus are better identified by using a simple prediction model than by relying exclusively on the results of a 2-hour oral glucose tolerance test. Although adding the 2-hour glucose variable to the model enhanced prediction, the resulting slight improvement entails greater cost and inconvenience.