In this paper, various kinds of algorithms are explained that include Support Vector Machine. The aim is to improve efficiency in different parameters by describing the classification approach for detecting diabetes. In this, it will predict diabetes with SVM.SVM will classify the data into positive and negative data points. In this, we predict the diabetes of Type 1and Type 2.Type 1is a type of diabetes that has no cure. Type 2 diabetes is common diabetes. It develops from child. Diabetes is the fastest growing problem with more health and economic results. The increasing rate is predicted to increase to 430 million. Different types of data mining techniques are used. With SVM it will predict better accuracy. When we will predict the result with SVM, it will give accuracy. With prediction of different parameters, we can predict the target value. With diabetes, there can be eye blindness, stress and many more can happen. With the help of data mining, we can aware about diabetes. In this paper, mention all the data mining techniques, types of classifiers. At the end, In this paper describes the diabetes types and what we have done and accuracy of the data. Type 2 diabetes is not easy to predict all the effects.