From the past decade, data mining is involved in many fields as well the tremendous work has carried out on the medical sectors to diagnose different diseases like heart strokes, kidney and diabetes. Many applications have been introduced in this manifesto, which can be classified in to two sets of branches: the policy development and the decision support analysis. Still there is a lack of work in decision-making section. Our paper has aim towards the set of decision-making through classification analysis forecast. Data mining approach has work on this manifesto for us to analyze and forecast the analysis for the better clinical decision-making process by machine learning classification and logistic regression modeling has used to forecast the outcome of dataset through classification. Our proposed aim compared the classification analysis of previous researchers work by weka classification of experimenter part and auto-weka guide for better predictions. Our path approaches the best analysis in prediction through forecast and present the comparison of different classification techniques applied on the data set.