Project Summary African Americans, like most Americans, have a low adherence rate to statin class of cholesterol lowering medications prescribed for cardiovascular disease primary prevention, which contributes to disproportionate cardiovascular disease (CVD) morbidity and mortality. African Americans experience a cascade of disparities in lipid evaluation and control due to a higher risk of being unscreened for dyslipidemia, not being prescribed a statin, and a higher rate of statin nonadherence. This study will use de-identified data from the largest longitudinal cohort in the history of the United States, the NIH All of Us Research Program, to investigate the use of Artificial Intelligence/Machine Learning (AI/ML) to improve cardiovascular disease preventive care among African Americans by predicting an individual’s risk of statin medication adherence; this will provide a critical opportunity for clinicians and health systems to deliver tailored point-of-care interventions that prevent onset of medication nonadherence. Lack of effective interventions for medication nonadherence is a major problem that worsens the ongoing chronic disease epidemic. This study aims to apply AI/ML methodology to develop predictive models to identify African Americans at risk of nonadherence to statin class of cholesterol lowering medications. In addition, this study will perform an analysis of the prevalence of disparities in cardiovascular disease prevent care with statins among the Black population and the White population enrolled in the NIH All of Us Research program.