1Mr. N. Lakshmi Narayana, 2Nakka Pavani, 3Rangisetty Sai Madhav, 4Pamidi Hanok 03 08 Agriculture plays a vital role in ensuring food security and supporting economic development However predicting crop yield accurately is a challenging task due to variations in soil conditions rainfall temperature humidity and other environmental factors Traditional farming methods mainly depend on farmers experience and historical practices which may not always provide reliable predictions To address these challenges the proposed AIBased Crop Yield Prediction and Smart Farming system utilizes Artificial Intelligence AI and Machine Learning ML techniques to predict crop yield and provide smart farming recommendations The system collects agricultural parameters such as soil type rainfall temperature humidity and crop information from the user and processes them using a trained machine learning model Based on the analysis it predicts the expected crop yield and suggests suitable farming practices including crop selection irrigation planning fertilizer usage and pest management The application is developed using Python Flask HTML CSS and Machine Learning technologies providing a simple and userfriendly web interface The proposed system improves prediction accuracy reduces manual effort optimizes resource utilization and supports sustainable farming practices It serves as an effective decisionsupport tool for farmers agricultural researchers and organizations by enhancing productivity and promoting datadriven agriculture Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026