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Nowadays, diabetes is a common disease that affects millions of people over the world, and women are mostly affected by this disease. Recent healthcare studies have applied various innovative and advanced technologies to diagnose people and predict their disease based on clinical data. One of such technologies is machine learning (ML) in which diagnosis and prediction can be made more accurately. In this paper, the designed model predicts the diabetes of females of Pima Indians heritage by taking the clinical dataset. Here, this problem is considered as a binary classification problem. Therefore, supervised learning algorithms have been used, such as classification tree (CT), support vector machine (SVM), k-Nearest Neighbour (k-NN), Naïve Bayes (NB), Random Forest (RF), Neural Network (NN), AdaBoost (AB) and Logistic Regression (LR). We use the female Pima Indians diabetic dataset from Kaggle …