• Tembe Madhura Mahendra
• Lale Suyog Bhagwan
• Parte Viraj Kiran
• Singh Rajver Bhajan
• Prof. Dr. Prashant P. Nitnaware

Agriculture forms the basis for supporting the economies of many countries across the globe. However, con- ventional agriculture faces a number of challenges, such as unpredictable climatic changes, inefficient water management, and limited access to technical support. Crops are frequently affected by diseases, and farmers are not able to accurately predict crop yields. Additionally, farmers are forced to wait for a long period to access government support. As a result, this paper seeks to address some of the above-mentioned issues by developing a smart agriculture system, dubbed Agri Predict, which utilizes artificial intelligence to carry out precision agri- culture. The smart agriculture system utilizes advanced machine learning algorithms to predict crop yields, detect crop diseases, and provide farmers with information on government programs and a buy/sell marketplace. As a result, farmers will be able to make informed decisions, reducing crop waste and increasing crop productivity.

Artificial Intelligence, Machine Learning, Smart Farming, Crop Yield Prediction, Precision Agriculture, Sustainable Agriculture

"AgriPredict: AI-Driven Smart Farming for Enhanced Crop Management and Yield Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 2, page no.c515-c522, February-2026, Available :http://www.jetir.org/papers/JETIR2602276.pdf

"AgriPredict: AI-Driven Smart Farming for Enhanced Crop Management and Yield Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 2, page no. ppc515-c522, February-2026, Available at : http://www.jetir.org/papers/JETIR2602276.pdf