Agriculture is one of the important aspects in the world, also the contribution of agriculture to the GDP of India increased to 19.9 percent in 2020-21 from 17.8 percent in 2019-20. Globally crop disease becomes a major cause of concern, so to overcome this concern a plant disease detector should be there which gives good results and increases the yield for farmers. In this scenario, the best option for dealing with crop disease identification is an Image Classification based disease detection system. The key goal of this project is to identify the disease in real-time by uploading an image of the infected plant leaf to the system. Aside from that, the system suggests remedies for the particular disease that is identified by the system. Our proposed research paper includes various phases of implementation namely data set creation, image pre-processing, image post-processing, and finally disease classification and grading. Overall, we are using machine-learning techniques to train the dataset and finding the disease for that particular plant.