Abstract: Chronic diseases such as cancer, diabetes, strokes, arthritis, and cardiac-related disease are the major and leading cause of high mortality and disability rates in India as well as worldwide. Developing a convincing and favorable solution for these diseases is the need of the hour. The development and Technological advancements in medical science have proved beneficial in detecting the initial stage among patients and providing accurate data analysis among them. The authenticity and accuracy of the diagnosis and consequent treatment depend upon the correct analysis of patients; incorrect diagnosis or overdiagnosis may lead to casualty. Therefore, at most care and precautions must be taken for the correct examination of illness or disease as misdiagnosis may result in the death of a patient. However, a Machine learning, Deep learning-based diagnostic system with high accuracy proposed here, can offer promising solutions to identify the correct & accurate cause of such chronic diseases. Machine Learning-based diagnostic systems can detect diseases such as Lung disease, brain tumors, Heart disease, Skin disease, diabetes, and prophecy of developmental stages in patients. A proper or suitable diagnostic system may prove helpful for doctors in reducing the high mortality rate among patients with these chronic diseases. Great work has to be done on the accurate diagnosis of many diseases. A lot of work has been done in this direction but no convincing solution for accurate diagnosis has been found till now with the help of machine learning Deep learning diagnostics systems we can identify the diseases as well as the developmental stages in many diseases such as Lung disease, Brain tumor, Heart disease, etc. In this way, we can reduce the mortality rate and save money lives. In these Research paper, we have explored various Machine learning and Deep learning algorithms for training and testing the different diseases in our system. With the help of Machine learning and deep learning techniques, we trained our various machine learning and deep learning models using various algorithms for each disease. In our Multidisease Identification and Prognosis system, we trained the model for five diseases i.e. Heart disease, Brain tumor, Skin disease, Lung disease, and diabetes. So, we have achieved 98% accuracy on Heart disease, 97% accuracy on Brain disease, 90% accuracy on Skin disease, 87% accuracy on Lung-related diseases, and 97% accuracy on diabetes with the help of different machine learning and deep learning algorithms in our Project We used different algorithms for trained the model like VGG 16, Dense Net, Res Net 50, Random Forest, Sequential to trained our multiple diseases model. In the end, we created the whole web application for easy and understandable user interaction and to fulfill the requirements of patients.