Climate change is a phenomenon that unequivocally alters natural systems in all regions of the world, particularly extreme variations in precipitation, which can have more severe and unexpected effects on hydrology and ecosystems. This study provides an overview of the extreme rainfall projection (2006–2100), using observed data (1970–2010), at Mascara station, located at the East of the Macta catchment (Northwestern Algeria). Four greenhouse gas emission concentration trajectory scenarios 2.6 W/m2 (RCP2.6), 4.5W/m2 (RCP4.5), 6W/m2 (RCP6.0), and 8.5W/m2 (RCP8.5), from CCSM4 model (Community Climate System Model, version 4) were downloaded from the German Center for IT Climate ( https://www.wdc-climate.de/ui/ ), on 11/20/2018 at 11:22 p.m. and then corrected for bias by the statistical downscaling method (SDM). The historical maximum daily rainfall at the Mascara station was collected from the ANRH of Oran (1970–2010). A spatial dependency function (SDF) was applied to estimate the CCSM4 data at the selected station (Mascara). Next, the latter has been corrected using the observed data parameters (mean and standard deviation). The results showed an underestimation of the extreme rainfall during the observed period. The fitting of extreme precipitation (observed and projected) to the generalized extreme value (GEV) showed good agreement with the optimistic scenario RCP2.6. This study provides complementary and coherent results on extreme rainfall in northwestern Algeria that local decision-makers can integrate into the development of disaster management plans and the planning of infrastructure adaptation.