In India, and over 30 million individuals possess diabetes, and many more are at risk. In order to prevent diabetes and the health issues it is connected with, early detection and treatment are necessary. This study tries to evaluate a person's risk of developing diabetes based on their lifestyle and family history. Different machine learning algorithms were used to predict the risk of Type 2 diabetes since these algorithms is quite accurate, which is crucial in the medical field. People can self-assess potential risk of diabetes that once model has been trained correctly accurately. 752 instances have been collected for the investigation through an offline and online assessment with questions pertaining concerning health, lifestyle, and family medical history. The Apache Indian Diabetes database also utilized the same algorithms. For both datasets, Random Forest Classifier is determined to perform at the highest level of correctness.