Welcome to SMART-Forage, the cutting-edge intelligent platform for multi-species forage silage fermentation quality prediction. Silage quality is jointly shaped by raw material properties, process parameters and environmental conditions. Built on a robust dataset from 505 academic papers, covering 79 forage species and 98 raw material categories (with silage-used parts classified), it leverages XGBoost, CatBoost and other advanced tree-based models to accurately predict key stabilization-stage indicators like pH, ammoniacal nitrogen, organic acids and nutrient retention rates. Input Day 0 parameters (raw material nutrients, process settings, environmental factors) for fermentation tier insights. Equipped with model interpretation, it reveals core influencing factors and optimal ranges, empowering scientific decisions to optimize processes and enhance feed quality.