Cassava is one of Africa’s most important crops found in tropical regions worldwide. As important as cassava is, concerns are raised towards its diseases. In this paper, the aim is to identify and classify images of cassava leaves into healthy and unhealthy (disease) categories using machine learning. The categories include; four(4) disease categories - Cassava Bacterial Blight (CBB), Cassava Brown Streak Disease (CBSD), Cassava Green Mite (CGM) and Cassava Mosaic Disease (CMD), and one (1) health category – Healthy. At the end of this implementation, we were able to train a model that classifies images of the given cassava leaves into one of the five(5) categories.