One of the biggest revolutions of modern history is the invention of agriculture for a healthier lifestyle. It significantly changed the human culture and played an important role in the development of the population and biological improvements in food production and domestication. Study into agriculture is then planned by improving the disease diagnostics method with the use of newer information technology to enhance efficiency and quantity for agricultural production and its allied operation. This project focuses on the identification and diagnosis of plant leaf diseases of tomatoes and pomegranate based on visual symptoms, anthracnose, and powdery mildew. Machine learning and image processing using SVM, KNN require many steps to identify and distinguish disease signs.