In India, most of the people are dependent on agriculture. The raw materials obtained from the agriculture are served as food for many people. The crop plantations are being destroyed because of the two main reasons: (i) The natural destructions such as drought, flood, famine, and earthquake. (ii) Pest and pathogens. About 98% of the destruction in crops are caused by pathogens and pests. The remaining 2% of the destruction is due to natural disaster in the surroundings. The rural farmers are severely affected by the crop production problems. In crop's life cycle, leaf plays a major role in getting the information about the growth and production of the plant. In this paper, the proposed system works on the preprocessing of the dataset. The leaf images are collected from the plant village dataset. The feature extraction is applied to the images during the data preprocessing stage. Convolution neural network (CNN) is used for the classification and detection of diseases. The recommendation of pesticides and fertilizers is done by using TensorFlow technique. The convolution neural network with various number of layers is used for training the model, and GUI screen serves as a user interface.