Accurate yield forecasts can improve sustainability in the sugarcane industry by delivering better environmental and economic outcomes. Foreknowledge of the size of the upcoming crop can influence fertilizer management, mill planning and maintenance and marketing decisions. Everingham et al. developed statistical models to accurately forecast sugarcane yield in Tully, Australia. These models used random forest datamining techniques to find relationships between yield, climatic indices and crop model outputs. They found that accurate yield forecasts were possible 8 – 14 months before the end of the harvest season.