Heart complaint remains one of the leading causes of mortality worldwide, making early discovery pivotal for effective treatment and forestallment. This design focuses on developing a prophetic model to identify the threat of heart complaint in individualities using machine literacy ways. By assaying patient data, including vital health pointers similar as age, blood pressure, cholesterol situations, casket pain type, and other applicable medical attributes, the model aims to classify individualities grounded on their liability of developing heart complaint. colorful bracket algorithms are applied and compared to determine the most accurate approach. The results demonstrate that machine literacy can serve as a dependable tool for aiding healthcare professionals in early opinion, enabling timely intervention, and eventually perfecting patient issues.