Agroecology emphasizes farming in harmony with natural systems, requiring farmers to understand ecological mechanisms such as soil fertility, water cycles, and biodiversity. To support this, researchers have applied the 13 principles of agroecology as a framework to evaluate farming practices and provide decision-making guidance. However, farmers often struggle to interpret these principles in daily operations. Artificial Intelligence (AI), Machine Learning (ML), and Big Data now offer practical solutions by translating complex ecological and economic information into simple, actionable advice. The EcoFarm mobile application, developed by WorldFish and the University of Engineering and Management (UEM), represents a pioneering effort to integrate AI into farmer decision-making. EcoFarm supports integrated rice–fish farming and other agroecological practices. The app provides real-time recommendations on soil health, water quality, irrigation scheduling, crop choices, fertilizer application, and pest management. By combining local data with predictive analytics, it helps farmers improve yields, optimize resources, and reduce costs. EcoFarm will functions as a digital advisor: it collects survey data, monitors key performance indicators (yields, soil quality, water quality, farmer income), and processes inputs through ML algorithms. Farmers receive simple or text-based guidance, such as when water quality is poor or when crops need timely intervention. This system reduces dependence on chemical inputs, promotes organic methods, and improves long-term soil and ecosystem health. By combining scientific models with local knowledge, the app empowers farmers to make informed choices, enhance productivity, and strengthen resilience against climate stress.