Diabetes Mellitus is a rapidly growing global health concern that poses significant risks, if not detected and managed at an early stage. This study aims to develop a model that accurately predicts diabetes mellitus using machine learning (ML) models, namely hybrid and ensemble models. Various natural remedies that have traditionally been used to manage diabetes have also been studied. Standalone machine learning algorithms were combined as hybrid and ensemble models. Performance metrices were used to evaluate the models. This integrated approach is a complete package for diabetes management, reducing the overall cost of this life-long disease.