The continuous pandemic has transformed the globe, resulting in a situation where the majority of previously manual tasks are now completed online. However, the method for determining the severity of an illness has remained unchanged. We want to develop an application that processes data, forecasts diseases, and assists in providing disease details before an emergency or catastrophe arises. The main goal of our project is to design a disease prediction application (Grampurohit and Sagarnal in Disease prediction using machine learning algorithms, 2020, [1]). The application detects the diseases based on symptoms. The system proposes a detailed classification about the fetched disease and provides the fetched disease details. For reliable disease prediction, we practice the system getting to know decision tree (DT) and logistic regression (LR). A collection of disease symptoms is required for disease prediction (Grampurohit and Sagarnal in Disease prediction using machine learning algorithms, 2020, [1]). The method is simple to use even for those with less medical understanding, and it can help with early disease identification and diagnosis. It can also help people who are hesitant to go to the doctor when they have minor symptoms. This will give them a general picture of the disease’s severity.