This document describes a machine learning model that predicts disease based on symptoms. It uses classification algorithms like decision tree, random forest, and naive Bayes. The model is built using Python libraries like NumPy, Pandas, Scikit-learn, and Flask. Symptoms are input by the user and preprocessed before being fed to the trained algorithms. The model outputs the most likely disease based on the symptoms. It aims to help physicians diagnose patients more accurately and efficiently.