Cardiovascular diseases (or heart diseases) are the leading cause of death worldwide, with around 18 million deaths yearly. Several diagnosis methods are available worldwide, but they are expensive in terms of time, money and personnel. The motivation for our project is to conduct data analysis and build classification models using machine learning techniques to help practitioners make more accurate decisions regarding classifying heart diseases. We aim to combine multiple models for data analysis and perform relevant model evaluation techniques to present a proper, functioning model.