heart disease is considered as one of the common health problem, and machine learning can be a powerful tool for reducing the burden of disease. Heart Disease Prediction Model using Machine Learning is a process of using algorithms to learn based on the data and produce some predictions about future events. The data used to train the several different sources of machine learning algorithms, including medical records, health insurance claims, and patient surveys. The predictions made by the machine learning algorithm can be used to help prevent heart disease by identifying risk factors and providing personalised recommendations for treatment and lifestyle changes. The heart disease prediction system correctly predicted heart disease in 96.7% of the test cases when using Random Forest model