One of the most important problems now affecting the globe is heart disease. A significant problem in the field of clinical knowledge analysis might be disorder prediction. Many medical conditions can be identified, detected and predicted using machine learning. This study uses machine learning methods and Python programming to study heart disease prediction. Heart disease has become a prevalent and fatal condition in the last few years due to the suppression of fat. Excessive pressure in the human body causes this disease to develop. Using multiple features from the dataset, researchers can predict heart disease. To assess patient performance, a dataset consisting of 12 parameters as well as 70000 unique data values ​​was used. The main goal of this study is to increase the accuracy of heart disease detection by using algorithms where the target output determines whether the subject has heart disease. This study provides the base for future heart disease prediction by using the machine learning method.