Data mining is considered one of the important phenomena in Knowledge Discovery in Database (KDD) process. In healthcare sector ample amount of data are available which is very essential to convert these data into useful and valuable. In this context data mining classifier algorithms play an important role to discover knowledge from big data.The objective of the present study is tocompare accuracy, sensitivity, specificity, and receiver operating characteristics of five classifier algorithms like Linear Discriminant Analysis (LDA), k-Nearest Neighbour (kNN), Support Vector Machine (SVM), Random Forest (RF), and Adaboostto predict diabetes.R is used to process data analysis. The SVM was recorded the best classifier with the accuracy of 0.7386, sensitivity0.8300 and specificity 0.5660, followed by LDA algorithm with accuracy of 0.732, sensitivity 0.8800 and specificity 0.4528 to predict diabetes.