This study investigates the long-term trends and seasonal dynamics of India’s cereal exports specifically Basmati rice, non-Basmati rice, other cereals, and wheat using trend modelling and decomposition techniques. Drawing on monthly export data from April 2006 to November 2024 (with wheat data beginning in 2013), linear, log-linear, and quadratic trend models were estimated alongside additive, multiplicative, and STL (Seasonal-Trend decomposition using Loess) seasonal models. Results indicate strong linear and exponential growth in Basmati and non-Basmati rice exports, wheat exports exhibited no statistically significant trend and displayed high volatility. Durbin-Watson statistics revealed serial autocorrelation in most models, highlighting the importance of incorporating seasonality and external shocks in trend analysis. Additive decomposition reveals pronounced seasonal effects in Basmati rice exports, STL analysis confirms these patterns. Wheat shows moderate seasonal strength, while non-Basmati rice and other cereals exhibit mild seasonality. These findings underscore the necessity of commodity-specific export strategies aligned with harvest cycles and global demand windows.