ABSTRACT Cardiovascular Diseases (CVDs) are the principal motive for a huge number of loss of life in the world over the previous couple of decades, about one character dies according to the minute because of heart sickness. So, theres a need for dependable and correct gadgets to diagnose such diseases in time for the correct remedy. Data technology was implemented to automate the evaluation of big and complex records inside the field of health care. The proposed work predicts the possibilities of Heart Disease and classifies the threat stage by way of imposing distinctive statistics mining strategies which include Naive Bayes, Decision Tree, and Logistic Regression. Data preprocessing and function selection steps have been done before constructing the models. The fashions were evaluated based totally on the accuracy, precision, bear in mind, and F1 score. The correct prediction of coronary heart ailment can prevent existing threats. The most important goal of this paper is to build an ML model for coronary heart disease prediction primarily based on the related parameters.