This repository is a Discrete Mathematics course project that contains code to predict heart disease based on clinical data. Heart Disease Risk Prediction is a machine learning‑based web application designed to analyze potential cardiovascular disorders using patient clinical features. It uses the Streamlit framework for an interactive interface, along with Python libraries such as Pandas for data processing, Scikit‑Learn’s Random Forest algorithm for prediction, and Matplotlib to visualize model performance. The modular code structure demonstrates practical applications of data science in early health risk detection.