Supervised and unsupervised learning mechanisms are two subcategories of machine learning techniques that use sample data to train mathematical models. It uses statistical methods to predict an outcome that can generate actionable insights. Predictive machine learning algorithms use historical data as input and apply different algorithms to the dataset to forecast the future. This study focuses on various classification algorithms and their performance analysis. Motivation behind this study is to identify the best classification algorithm that can provide the most precise results based on performance metrics. In this study, eight classification algorithms are compared to determine the optimal approach for the early detection of diabetes using a specific diabetes dataset. The analysis performed in this study provides the research directions to the researchers for further work in this area.