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Abstract We developed a model to compare the impacts of different lifestyle interventions among prediabetes individuals and to identify the optimal age groups for such interventions. A stochastic simulation was developed to replicate the prediabetes and diabetes trends (1997–2010) in the U.S. adult population. We then simulated the population-wide impacts of three lifestyle diabetes prevention programs, i.e., the Diabetes Prevention Program (DPP), DPP-YMCA, and the Healthy Living Partnerships to Prevent Diabetes (HELP-PD), over a course of 10, 15 and 30 years. Our model replicated the temporal trends of diabetes in the U.S. adult population. Compared to no intervention, the diabetes incidence declined 0.3 per 1,000 by DPP, 0.2 by DPP-YMCA, and 0.4 by HELP-PD over the 15-year period. Our simulations identified HELP-PD as the most cost-effective intervention, which achieved the highest 10-year savings of $38 billion for those aged 25–65, assuming all eligible individuals participate in the intervention and considering intervention achievement rates. Our model simulates the diabetes trends in the U.S. population based on individual-level longitudinal data. However, it may be used to identify the optimal intervention for different subgroups in defined populations.