Accurate climate predictions help policymakers mitigate the negative effects of climate change and prioritize environmental issues based on scientific evidence. These predictions rely heavily on the outputs of GCMs (General Circulation Models), but the large number of GCMs and their different outputs in each region confuses researchers in their selection. In this paper, we analyzed the performance of a CMIP6 (Climate Model Intercomparison Project Phase 6) multi-model ensemble for precipitation data over Northern Europe. We first evaluated the overall performance of 12 CMIP6 models from GCMs in thirty years of 1985-2014. In addition, future projections were analyzed between 2071 and 2100 using SSP1-2.6 and SSP5-8.5 (Shared Socioeconomic Pathways). Then, simulations were statistically improved using an ensemble method to correct the systematic error of the CMIP6 models and then the capacity of postprocessed data to reproduce historical trends of climate events was investigated. Finally, the possible spatio-temporal changes of future precipitation data were explored in Tana River Basin. The results of this study show that different CMIP6 models do not have the same accuracy in estimating precipitation in the study area. However, the ensemble method can be effective in increasing the accuracy of the predictions. In addition, this study projected a change in the monthly precipitation data over Tana River Basin by 2.46% and 2.06% from 2071 to 2100 compared to the historical period, based on SSP1-2.6 and SSP5-8.5, respectively.