A vast amount of data is generated in the fields of healthcare and diagnostics, doctors have to make a direct contact with patients to determine the wounds, injuries and diseases by which the patient is affected. This paper highlights the application of classifying and predicting a specific disease by implementing the operations on medical data generated in the field of medical and healthcare. The proposed system can solve difficult queries for detecting a particular disease and also can assist medical practitioners to make smart clinical decisions which traditional decision support systems were not able to. The decisions taken by medical practitioners with the help of technology can result in effective and low cost treatments. In this paper, data mining methods namely, Naive Bayes and J48 algorithms are compared for testing their accuracy and performance on the training medical datasets.