Machine Learning is used across many spheres around the world. The healthcare industry is no exception. Machine Learning can play an essential role in predicting presence/absence of locomotor disorders, Heart diseases and more. Such information, if predicted well in advance, can provide important insights to doctors who can then adapt their diagnosis and treatment per patient basis. The healthcare industry collects large amounts of Healthcare data, but unfortunately not all the data are mined is required for discovering hidden patterns and effective decision making. In this project, we will be predicting potential Heart Diseases in people using Machine Learning algorithms. The algorithms included are K Neighbours Classifier, Support Vector Classifier, Decision Tree Classifier and Random Forest Classifier. We will analyse prediction systems for Heart disease using a greater number of input attributes. The system uses medical terms such as Sex, Age, blood pressure, cholesterol like 13 attributes to predict the likelihood of patient getting a Heart disease.