Apples possess diverse nutritional values and can be processed into a extensive range of products, holding substantial potential to enhance public health. However, a critical knowledge gap exists regarding the impacts of meteorological factors on apple quality, which limits the optimization of apple production especially in China, the world's largest apple producing country. Integrating biophysical and machine learning models, our study utilized the process-based biophysical model STICS to simulate 'Fuji-based' apple quality indicators, including single fruit weight, soluble solid content (SSC), titratable acidity (TA), and the SSC/TA ratio, across China's apple planting regions. We further identified potential high-quality regions based on these quality indicators and quantified the contributions of meteorological factors to apple quality using random forest method based on simulation data of STICS model. The STICS model achieved good performance in simulating apple quality indicators, with normalized root mean square errors (NRMSE) consistently below 25 %. High-quality apple planting regions were primarily concentrated in the Loess Plateau and Bohai Bay Rim areas that benefit from favorable climatic conditions for apple cultivation. The random forest model exhibited robust performance, with NRMSE consistently below 11.2 % and R2 values exceeding 0.88 for each apple quality indicator. Effective accumulated temperature greater than 5 degrees C during fruit setting to maturity was identified as the most important meteorological factor, contributing over 30 % to each quality indicator and highlighting potential inter-varietal differences in apple quality. Average solar radiation, minimum temperature, average temperature, and relative humidity were found to have significant impacts on specific quality indicators: single fruit weight, soluble solid content, titratable acidity, and the SSC/TA ratio, respectively. This combined approach provides promising insights for evaluating the impacts of meteorological factors on apple quality, optimizing apple planting layouts, improving fruit quality, and developing potential strategies to adapt to climate change.