Diseases of plants are conditions or illnesses that adversely affect the growth and general well-being of plants. The pathogens that can cause these diseases include bacteria, viruses, fungi, nematodes, and protozoa. Environmental variables such as poor soil conditions, severe temperatures, drought, and pollution can also play a role in the development of these diseases. Plant diseases can have a substantial influence on both the productivity of agriculture and the safety of food supplies. They are capable of lowering crop yields, lowering the quality of fruits and vegetables, and even killing entire plants along their path of destruction. Some plant diseases can also spread quickly, which can result in epidemics that have the potential to wreak havoc across large regions or even countries. In order to effectively manage plant diseases, it is often necessary to employ a combination of disease preventive, monitoring, and control strategies. During the course of this inquiry, we collaborated with restnet18 to construct a machine learning model, and it ended up achieving an accuracy of 99.6%. This level of precision is attainable because to the dataset's inherent balance as well as its capacity for hyper tuning. After compiling the 33 images into a single test set, we put that test set through our trained model's paces to see how well it performed. According to the findings, our trained model achieved an accuracy rate of one hundred percent across all 33 photos.