European climatic change has been proposed to induce many changes to forests, about factors such as tree species distributions, site productivity, groundwater availability, outbreaks of forest pests, and damage from wind-breakage of trees. Novel approaches to empirical tree growth modelling using re-measurements over large climatic gradients capture variability associated with long-term climatic conditions as well as weather during the growth period. Using the latest version of the individual tree-based forest simulator, PrognAus, which has been outfitted with a climate-sensitive basal area increment module, we forecast growth of trees in pure and mixed stands of Pinus sylvestris L. and Quercus spp. across a network of 23 European sites between 2017 and 2100 under current climate and RCP 4.5 and RCP 8.5 climatic scenarios. By training a stand-level static reduced model (SRM) from these local level results, we forecast widespread future growth changes for stands of Pinus sylvestris and Quercus spp. across Europe. Our SRM predicts stand gross-volume relative growth (ratio of the gross volume production in a given growth year to the gross volume production until the start of the growth year) with a generalized additive mixed model (GAMM). We decomposed overall growth into tensors capturing variation associated with stand species mixture type (pure P. sylvestris, mixed P. sylvestris- Q. spp., pure Q. spp.), age, and weather conditions during the growth year and the preceeding year. Wall-to-wall predictions based on the SRM are presented for a high-resolution 30-arcsecond grid spanning most parts of Europe.