 This research used machine learning techniques to identify county phenotypes of premature cardiovascular mortality, PCVM. It found that high-risk phenotypes were more likely to occur in counties with lower income, less physical activity, and higher levels of food insecurity. Additionally, it identified other risk factors such as broadband access, smoking, SNAP benefits, and education level. Based on this research, interventions for reducing PCVM should be tailored to the specific county phenotype and geographical area.