Diabetes stands as one of the foremost causes of mortality in the United States. The imperative to predict diabetes in the country arises from its widespread prevalence, substantial healthcare expenses, potential severe complications, and the prospect of proactive prevention and early intervention. This study leverages data from the Framingham study to investigate the utilization of machine learning models in the realm of diabetes prediction. Consequently, the implementation of predictive models to combat diabetes holds the promise of yielding substantial positive outcomes for public health, optimizing healthcare resource allocation, and enhancing the overall health and welfare of individuals and communities.