Plant diseases can have a devastating impact on crop yields, leading to significant economic losses for farmers and threatening global food security. To address this challenge, an Android application has been developed using a combination of machine learning and API technology to accurately identify and diagnose plant diseases. The application uses a machine learning model trained on a large dataset of plant images, allowing it to recognize and differentiate between various diseases affecting crops. Users simply upload a photo of the affected plant, and the app provides a diagnosis along with recommendations for treatment. The app also integrates with an API to securely store user data and provide personalized recommendations for managing plant health. This data can include information such as the user's location, soil type, and environmental conditions, which can all have an impact on plant health. The app can use this data to provide recommendations for specific treatments or crop varieties that are better suited to the local environment. By providing a fast and accurate diagnosis of plant diseases, this application can help farmers and gardeners take proactive measures to protect their crops and improve yields. The app can also promote sustainable agriculture practices by reducing the use of pesticides and other harmful chemicals. Overall, this tool has the potential to play a significant role in addressing the global challenge of plant disease and promoting sustainable food production.