This project addresses the global health challenge posed by glaucoma through the development of an innovative Python-based application. Utilizing advanced machine learning techniques, specifically the VGG16 model with transfer learning, the application aims to enhance glaucoma diagnosis and management. By automating glaucoma severity classification into distinct categories, including No_DR, Proliferate_DR, Mild, Moderate, and Severe, the application provides personalized medical advice tailored to the predicted severity. The user-friendly interface, powered by the Tkinter library, enables individuals to upload eye images for real-time analysis, empowering them to actively monitor their eye health. Through early detection and informed decision-making, the application strives to slow down the progression of glaucoma and enhance overall quality of life. This project exemplifies the intersection of technology and healthcare, promising to positively impact lives by promoting early awareness and proactive glaucoma management.