Rice is one of India's most extensively farmed crops, and it can be infected with a number of diseases at different stages of development. Due to their lack of understanding, farmers find it extremely difficult to manually diagnose these diseases. We created our own dataset and generated our deep learning model using Transfer Learning because a collection of rice leaf disease photos was not freely available. The proposed cnn architecture was trained and tested using data from different sources, and it is based on VGG-16. The precision of the proposed model is 92.46 percentage. We also showed why and where it occurs, its symptoms and remedies for making it easy for the agriculturists.