Simulations of crop yield due to climate change vary widely between models, locations, species, management strategies, and Representative Concentration Pathways (RCPs). To understand how climate and adaptation affects yield change, we developed a meta-model based on 8703 site-level process-model simulations of yield with contrasting future adaptation strategies and climate scenarios for maize, rice, wheat and soybean. We tested 10 statistical models, including some machine learning models, to relate the percentage change in future yield relative to the baseline period (2000-2010) to explanatory variables related to adaptation strategy and climate change. We used the best model to produce global maps of yield change for the RCP4.5 scenario and identify the most influential variables affecting yield change using Shapley additive explanations. For most locations, adaptation was the most influential factor determining the yield change for maize, rice and wheat. Without adaptation under RCP4.5, all crops are expected to experience average global yield losses of 6–21%. Adaptation alleviates this average loss by 1–13%. Maize was most responsive to adaptive practices with a mean yield loss of -21 % [range across locations: -63%, +3.7%] without adaptation and -7.5% [range: -46%, +13%] with adaptation. For maize and rice, irrigation method and cultivar choice were the adaptation types most able to prevent large yield losses, respectively. When adaptation practices are applied, some areas may experience yield gains, especially at northern high latitudes. These results reveal the critical importance of implementing adequate adaptation strategies to mitigate the impact of climate change on crop yields.