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Abstract: The development of modern technologies such as data science and machine learning has paved the way for healthcare communities and medical institutions to detect diseases as early as possible and contribute to better patient care. The accuracy of detecting possible diseases will be reduced if we do not have complete medical data. Also, certain diseases are based on regions, which could lead to poor disease prediction. Our body shows the symptoms when something bad happens in our body, sometimes it can be a small problem but sometimes we can have a serious illness and if we don't take care of these symptoms early it can be too late for the to cure the disease. Therefore, we propose a disease prediction system that can predict possible diseases based on symptoms so that you can be cured at an early stage. It saves the time required to make the full diagnosis of the patient we can diagnose the patient for only the required diseases. In this work, we use machine learning algorithms that try to accurately predict possible diseases. The results generated by the proposed system have an accuracy of up to 87%. The system has incredible potential to anticipate possible diseases even more precisely. The primary purpose of this Study is to help non-technical staff and first-year physicians form proper opinions about disease.