Data Mining is an attractive and impressive tool for obtaining valuable knowledge from the vast amount of available data that can be used further for taking right decisions. A number of means and approaches are available for deriving profitable outcomes from the possible data. Mining of data by applying if-else rule has conventionally used for the objective of reveling rules in medical applications. The detection of distinct disease such as diabetes, heart attack etc. from large number of guess and evidences is a subject of great interest for the researchers which is not free from false assumption and unpredictable outcomes. Hence there was terrific requirement to utilize the valuable conclusions resulting from the information of the patients gathered in our data storehouse. Many predictors had worked for improving the result of the disease prediction systems using the approach of data mining. The systems are designed for predicting single as well as different diseases still there is probability for improving the result of the currently used disease prediction system in terms of accuracy and efficiency. Here, we have presented an analysis of current data classification algorithms and will encounter the chances of occurrence of distinct diseases on the basis of data stored in our database.