One of the most significant crops and food sources in world is wheat. However, the Growth of wheat is impacted by many diseases of the wheat leaf and many climatic factors. For various types of disease management, farmers detect disease with naked eye, which take lot of time and leads to unhealthy performance, therefore, there is an urgent need of advanced agricultural technology which can automatically and accurately detect the diseases of wheat crop. For our work, VGG19 is a type of CNN model utilized with transfer learning approach for recognizing diseases in wheat leaf images. The parameters of the proposed model is optimized for the classification task and obtained a good accuracy of 98.12%.