The objective of this work is to analyze the spatial distribution of biases of nine (9) regional climate models (RCMs) and their ensemble average used under the framework of COordinated Regional climate Downscaling EXperiment (CORDEX) project over West Africa during the summer period. We assessed the ability of RCMs to represent adequately West African summer rainfall by analyzing some statistical parameters such as the relative bias, the standard deviation, the root mean square error (RMSE) and the correlation coefficient between observation data (GPCP used as reference) and regional climate models outputs. We first analyzed the relative bias between GPCP climatology and the other available observed data (CRU, CMAP, UDEL, GPCC, TRMM and their ensemble mean). This analysis highlights the big uncertainty on the quality of these observed rainfall data over West Africa which may be largely due to the rarity of in situ measurement data over this region. The statistical analysis with respect to GPCP rainfall shows the presence of large relative bias values over most part of West Africa for engaged RCMs. However their ensemble mean outperforms individual RCMs by exhibiting the weakest relative change. The RMSE values are weak over West Africa except over and off the Guinea highlands for RCMs and the Era-interim reanalysis. The spatial distribution of the coefficient of correlation between the observation data and RCMs shows that all models (except HIRHAM) present positive values over the Northern Sahel and the Gulf of Guinea. The model of the DMI exhibits the weakest values of correlation coefficient. This study shows that RCMs simulate West African climate in a satisfactory way despite the fact that they exhibit systematic biases.