This research work presents a decision making of healthcare operational system by using machine learning classifiers algorithm to predict the decision making in comparison to the actual decision making. This model may help to doctor for making the best decisions. This model helps us to prediction of indicators/diagnosis of cervical cancer. This study explains utilization of machine learning algorithms in determination of medical operation methods. This dataset focuses on the prediction of indicators/diagnosis of cervical cancer. The results show that SMO in RBF Kernel parameter for this case study generates highest accuracy level of 87.5%.