IJIRCSTJournal International Journal of Innovative Research in Computer Science and Technology I S Volume 14 Issue 1 Computer Science English January - February 2026 N N Y 2026 01 12 Computer Sciences A Climate-Resilient Agriculture Framework Using Machine Learning and Web-Based Decision Support Systems English Y 71 78 Pradeep GS English Y Amshu HU English N Apoorva Bhagwath English N Ashwath S English N Manu Sagar English N https://doi.org/10.55524/ijircst.2026.14.1.9 This result suggests the new model helps farms adapt to climate shifts by cutting down on crop dangers, boosting planning precision, one step at a time. This system provides practical benefits and recommends through a user-friendly interface accessible on low-bandwidth networks. Crop disease detection, weather-based crop recommendation, and market trend analysis, along with a multilingual chatbot for farmer assistance is integrated by machine learning models in this proposed system. Plant diseases from leaf images are identified by using Convolutional Neural Networks, while regression and time-series models assist in climate and market analysis. Agricultural production face challenges in farming due to climate change, irregular rainfall, rising temperatures, frequent pest outbreaks, and changing market conditions. This paper clearly gives the insights about the web-based climate-resilient agriculture system designed to support informed decision-making using data-driven techniques. English Machine Learning, Agriculture, Sustainable Farming, Weather Forecasting, Climate Resilience https://ijircst.org/abstract.php?article_id=1437