Abstract : There are numerous machine learning approaches that can perform predictive analytics on vast volumes of data in a range of businesses. Although using predictive analytics in healthcare is challenging, it will eventually help practitioners make quick choices about the health and treatment of patients based on vast amounts of data. Globally, diseases including liver disease, diabetes, kidney diseases, cancer and heart-related diseases are responsible for a large number of fatalities, however the majority of these deaths are the result of improperly timed disease check-ups. Due to a lack of medical infrastructure and a low doctor-to-population ratio, the aforementioned issue exists. According to data, India has a doctor-to-population ratio of 1:1456 compared to the WHO's suggested ratio of 1 doctor to 1000 patients, demonstrating a physician shortage. If not identified early, diseases including diabetes, liver, kidney, cancer and heart disease pose a risk to humanity. As a result, many lives can be saved by early detection and diagnosis of these disorders. The main goal of this research is to use machine learning classification algorithms to anticipate dangerous diseases. Diabetes, heart disease, liver, cancer and heart diseases are all covered in this study. Our team developed a medical test online application that uses the idea of machine learning to make predictions about various diseases in order to make this run smoothly and be accessible to the general public. Our goal in this effort is to create a web application that uses machine learning to forecast numerous ailments, such as liver, diabetes, kidney, cancer and heart disorders.