Forest anthropogenic and natural stand-replacing disturbances are increasing worldwide due to global change. Many uncertainties regarding the regeneration and growth of these young forests remain within the context of changing climate. In this study, we investigate the effects of climate, tree species composition, and other landscape-scale environmental variables upon boreal forest regrowth following clearcut logging in eastern Canada. Our main objective was to predict the effects of future climate changes upon post-logging forest height regrowth at a subcontinental scale using high spatial resolution remote sensing data. We modeled forest canopy height (estimated from airborne laser scanning [LiDAR] data over 20 m resolution virtual plots) as a function of time elapsed since the last clearcut along with climate (i.e. temperature and moisture), tree species composition, and other environmental variables (e.g. topography and soil hydrology). Once trained and validated with ∼240 000 plots, the model that was developed in this study was used to predict potential post-logging canopy height regrowth at 20 m resolution across a 240 000 km2 area following scenarios depicting a range of projected changes in temperature and moisture across the region for 2041–2070. Our results predict an overall beneficial, but limited effect of projected climate changes upon forest regrowth rates in our study area. Stimulatory effects of projected climate change were more pronounced for conifer forests, with growth rates increasing between +5% and +50% over the study area, while mixed and broadleaved forests recorded changes that mostly ranged from −5% to +35%. Predicted increased regrowth rates were mainly associated with increased temperature, while changes in climate moisture had a minor effect. We conclude that such growth gains could partially compensate for the inevitable increase in natural disturbances but should not allow any increase in harvested volumes.