Maize, is consumed globally as it is a staple crop. It is used widely everywhere. Despite its uses, it is prone to a variety of diseases which affect the yield and production of food also. It is important to timely detect these diseases so that the harm to the crop is minimal and the overall crop is not affected. Timely detection not only helps to protect the crop but it is also useful to the farmer and the economy as a whole. Earlier, farmers used to detect the diseases with naked eyes. This approach was time consuming, involved a lot of effort and its results were not that good because all the diseases can’t be detected with naked eyes. Disease detection actually requires a lot of expertise. Nowadays, Machine Learning and Deep Learning Techniques have progressed a lot and these techniques are widely contributing to the field of Plant Pathology, particularly, in disease detection, and their management. Using Machine Learning and Deep Learning, diseases of the Maize Plant can be detected in an efficient way which is time saving. These techniques are can help in better disease identification, disease management which in turn helps to manage crop and improve overall yield. This chapter covers some of commonly found diseases of the maize plant, describing the causes of these diseases and the outcomes of these diseases are also discussed. Apart from this, various challenges in detecting diseases of Maize plants and using deep learning for the identification of diseases, applications and future directions of deep learning in the field of Plant pathology are discussed.