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Now-a-days, there are endless machine learning techniques to predict and analyze the machine learning algorithms. In healthcare, the difficult level is ultimately increasing the work to the doctors to who are in the handling the decisions to update the patient's health and treatment on huge data. This paper discusses machine learning methods that should be analyzed in research work. For experimental approach, the patient medical records and their data are added with different machine learning algorithms and their accuracy are measured by the performance analysis. Algorithms like DecisionTree, Random Forest, and K-Nearest Neighbors Classifiers are used to predict whether the patient is having diabetics or not. The aim of this paper to be useful for the doctor to predict the early stages of diabetics using machine learning techniques.