Agriculture plays a major role everywhere because humans cannot be left without food in their lives. Many people depend on agricultural cultivation, either directly or indirectly. Leaves actually play an important role in the fast-growing of crops and give a good product but they are facing a major issue of low productivity because of plant leaf disease. Leaf disease occurs due to bacteria, viruses, fungi, pests, and so on. Detecting leaf disease plays an important role in increasing crop productivity. Manual detection is a time-consuming process. This chapter proposes automatic detections using machine learning and image processing techniques for detecting leaf disease. Machine learning techniques are better when compared with image processing techniques. Machine learning classification techniques are very helpful and quickly identify diseases. Machine learning using various classification techniques and evaluation metrics such as accuracy, precision, recall, and F1-Score will show disease progress on the leaf.