Drone technology is an emerging technology that is being used for many commercial and survey purposes. This research work has designed a drone technology to develop leaf disease detection and analysis system for agricultural applications. In general, UAV is also known as 'DRONE'. A drone is a device operated without a human pilot and can be remotely controlled with the help of a computer and radio frequency transmitter-receiver system. Identification of plant diseases plays a crucial role in preventing the loss of the yield and quantity of agriculture. A visually observable pattern on leaves helps to study the diseases in plants. Agricultural drones are highly efficient and their usage has been expanded to many areas in agriculture including fertilizer spraying, sowing seeds, growth monitoring, and mapping. This system includes the process of capturing images of the leaves automatically by using a drone with a raspberry pi-camera interface, so that it captures the images for image processing and analysis of leaf properties which would help to detect disease. The suitable algorithms of machine learning (ML) are used after performing feature extraction in the image processing techniques. The edge detection and histogram equalization techniques are used to extract features from the leaf. Drones can also be used in various agricultural applications to reduce human efforts and work time. With the help of GSM, information regarding leaf disease can also be given to the farmer at an early stage and avoid loss in crop production.