This project aims to build a new optimized ensemble model by blending a logistic regression model with two Support Vector Machine models. The model predicts three diseases- Diabetes, Heart disease, and Parkinson's. It analyzes the symptom-related data provided by the user as input and predicts whether the user has that particular disease or not with an accuracy rate of 77.27%, 81.96%, and 87.17% for Diabetes, Heart Disease, and Parkinson's disease respectively.