Human civilization is completely reliant on plants to provide our dietary needs. Despite having a population of over seven billion people that is rapidly expanding, our cultivable land has declined rather than increased. Plants, on the other hand, are susceptible to a variety of illnesses. Leaf disease, which comprises leaf spots, bacterial spots, black spots, and other conditions, is one of them. Bacteria and fungi are the most common causes of these disorders. This has an evident negative effect on the plant in the long run. As a result, it should be recognized early in order to save the crop’s productivity. We choose to focus on tomato leaf disease especially in our study report. Where we have used transfer learning technology to detect early blight, late blight, bacterial spots, and a few other diseases in tomato leaves images. Inception-V3 model has been deployed to have the best predictive outcome from the dataset which includes ten sets of tomato leaf images. The training and testing accuracy of transfer learning based inception-V3 model is 99.58% and 97.19% respectively. We also compare our model with other three transfer learning model which are VGG19, MobileNet and ResNet50.