ABSTRACT Benitez Kimberly P., Bondoc Franchesz Millen L., Department of Computer Studies, and Automation- College of Engineering and Computer Studies, Pampanga State Agricultural State University, Magalang Pampanga. JUNE 2023. "MOBILE-BASED CORN LEAF PEST IDENTIFICATION USING IMAGE PROCESSING". Adviser: Prof. Gemmarie M. Tapnio This study is entitled "Mobile-Based Corn Leaf Pest ldentification Using Image Processing." The study met its objectives based on the survey. The study aimed to help the farmers identify pests that ruin their crops and provide suggested pesticides that will prevent them. Additionally, the application is offline, so farmers can use it even with a poor connection. The application provides library features and a guide. Using different methods and procedures, researchers were able to define and analyze the problem and its solutions. The agile method of research was used in the development of the system; the researchers used the six phases: plan, design, develop, test, deploy, and review. Researchers used the following instruments to gather information for the study: internet research, interviews, and questionnaires. After colecting all the data, the researchers concluded that their objectives were met based on the survey. Three (3) IT experts at Pampanga State Agricultural University strongly agree with the system. Twenty-five (25) farmers at Cruzian strongly agree with the system. Five (5) crop science professors at Pampanga State Agricultural University strongly agree with the system. The IT experts from Pampanga State Agricultural University evaluated the functions of the system, and they strongly agreed, with an average of 3.55. The application is functional based on the statements given in the survey. The researchers tabulated the farmer's responses in Cruzian with an overall mean of 3.61, which means they strongly agree with the system. The crop science professors also give feedback with an overall mean of 4, and they strongly agree with the application.