Food and garden waste are important components of organic fraction municipal solid waste (OFMSW), representing carbon and nutrient rich resources composed of carbohydrates, lipid, protein, cellulose, hemicellulose, and lignin. Despite progressive diversion from landfill, over 50% of landfilled MSW is biodegradable, causing greenhouse gas emissions. In conventional waste management value chains, OFMSW components have been regarded as byproducts as opposed to promising resources with energy and nutrient values. Full exploitation of waste resources calls for a value chain transformation toward proactive resource recovery and waste commoditization. This requires robust projection of OFMSW composition and supply variability. Gradient boosting models are developed here using historical socio-demographic, weather, and waste data from U.K. local authorities. These models are used to forecast garden and food OFMSW generation for each of the 327 U.K. local authorities. The developed methods perform particularly well in forecasting garden waste due to a greater link to measurable environmental variables. The research highlights the key influences in waste volume prediction and demonstrates the difficulty in transferring models to local authorities without training data. The predictive performance and spatial granularity of model projections offer a promising approach to inform decision-making on future waste recovery facilities and OFMSW commoditization.