Using XGBoost, Decision Trees and Random Forest, I predicted whether a patient would have a Cardio Vascular Disease based on their previous medical records such as their ages, cholesterol levels, resting blood pressure, and electrocardiogram results. The data is collected from Kaggle.com. I used Pandas, NumPy, Matplotlib, Sklearn libraries, and had to apply data cleaning and analysis and various machine learning skills. Utilizing three advanced supervised machine learning algorithms from Sklearn, I conducted a comprehensive analysis to identify patterns that could act as signs of Cardio Vascular Diseases and successfully built a predictive model achieving around 90% accuracy rate.