Numerous industries employ machine learning approaches, and the healthcare sector is benefiting substantially through machine learning prediction approaches in particularly. Since predicting sickness is a challenging undertaking, automating the process is essential to minimize risks and notify the patient in advance. Accurate prognoses of their patients’ illnesses are necessary for doctors. In addition, a key component influencing treatment choices for precise forecasts is timing. Predicting diseases early on has grown in importance. Still, it is challenging for physicians to anticipate with any degree of accuracy from symptoms alone. Predicting sickness accurately is the hardest task. The application of machine learning in the realm of medical diagnosis is growing. This has been mostly credited to developments in illness categorization and identification systems, which can generate data that helps physicians, identify fatal diseases promptly and greatly improve patient survival rates. This research presents an intelligent healthcare program capable of disease prediction as well as data provision.