One primary purpose of regional simulation is to predict the spatial yield variation and temporal yield fluctuation, with presently available geographical database. Most crop models are site-specific, and some researches have attempted to up-scale the crop models for regional simulation. However, few have emphasized on their performance and uncertainties. The performance of regional simulation in China was evaluated in this study, and CERES-Rice model was employed in the simulation. In order to assess the suitability of model application for environments in China, we first calibrated the crop model at plot scale over main rice areas. Second, we calibrated and validated the CERES-Rice model at regional scale using the statistic of RMSE, cultivar coefficients and management practices were aggregated into each sub Agro-Ecological Zone (AEZ). Last, for analyzing the performance of the regional simulation, we simulated the historical (1981-2000) rice yield at 50 km 50 km grid scale, and compared the simulated with census values. Results show: the pattern of yield variation captured by model in most of the rice areas, especially in the main rice planting regions, i.e. AEZ 1-4 (over 95% of the total rice cultivation area), with RMSE< 22%. Some regions showed bad results, i.e. AEZ 5 and 6 with RMSE% 24%-30%. Simulated year-to-year yields matched well with the census values. 71.01% of simulation grids showed a bias less than 30%, most of them concentrated in the main rice planting areas. Therefore, the regional simulation is able to produce a reasonable estimation in spatial yield variation and temporal yield fluctuation, it can be used as a tool to provide information for policy makers at macro scale. There were various sources of uncertainty in the study and were analyzed in the discussion section.