This project introduces a smart system for spotting plant diseases using deep learning, specifically Convolutional Neural Networks (CNNs). The goal is to help farmers detect and address diseases affecting crops more effectively. We built the model using a tool called Keras, organizing data based on images of plants. The model learns from these images to recognize signs of diseases. Think of it like teaching a computer to identify plant health issues from pictures. The model has different layers which works together. Some layers help identify features, like patterns or colors in the images. Others decide if those features point to a disease. It's a bit like how our brains recognize shapes and colors. To train the model, we used a bunch of plant images labeled with their respective diseases. The model learns from these images and gets better at spotting diseases over time. The results show that our model is pretty good at this task. It can quickly and accurately identify diseases in plants, which could be a big help for farmers. This project is a step toward making farming more efficient and helping crops stay healthy.