Paddy is considered one of the top food items across the world. So, it usually gets more priority to save it from various diseases to prevent the loss of the farmer. Only proper identification can be a key tool to protect crop, increasing yield and reduce the losses. Technical tactics the use of machine getting to know and computer vision are actively researched to obtain intelligence farming through early detection of paddy ailment. A mobile software is manifestly ideal to resource the farmers in diagnosing what kinds of illnesses a paddy has. Although some similar applications exist, most of them achieve the function by submitting the image to a team of plant pathologists or expert garden advisors to get possible identification results and some advice. This have a look at presents the research, design, and implementation of a mobile software that could mechanically pick out the paddy sicknesses based on its leaf look with some pc imaginative and prescient and system getting to know approach. Many experiments and reviews on exceptional segmentations, characteristic extractions, and classification methods had been performed to locate the simplest method. The target institution of the consumer is individuals who request an unfastened and brief analysis of common paddy disorder at any time of the day.