Cardiovascular disease (CVD) is the leading cause of death in the United States (US) and places a heavy economic burden on the healthcare system. Recognizing the importance of CVD prevention, in recent years the American Heart Association (AHA) began to emphasize the need to increase awareness of key risk factors of CVD and proposed a new concept called ideal cardiovascular health. Based on this concept, we developed an agent-based model that is designed to capture individual health progression and study emergent CVD-related population health outcomes (diabetes, myocardial infarction, stroke and death) over a specified time period. We present some preliminary numerical results, which demonstrate the predictive validity of the model and show how the model could be used in practice by assessing the impact of a set of hypothetical lifestyle interventions on CVD-related health outcomes. Our model is designed to help policy-makers assess and compare different intervention programs targeting CVD prevention for the population of their interest.