Species distribution models (SDMs) are often used to predict the impact of climate change on the future distribution of species. However, the application of species-level SDMs often ignores intraspecific variation and can be problematic. The aim of the study was to incorporate intraspecific information into SDMs and compare predictions of subspecies- and species-level SDMs in a widespread African tree species, Sclerocarya birrea (marula). We used bioclimatic variables and terrain roughness index to calibrate nine algorithms in ‘biomod2’ platform. Ensemble models were built to predict the current and future suitable habitat of marula and separately its three subspecies, birrea , caffra and multifoliolata . Projections were made to 2041 − 2060 and 2081 − 2100 under three general circulation models and two shared socio-economic pathways. Results showed an expansion of the suitable habitat of marula as well as subspp. birrea and caffra in the two future time periods. The suitable habitat of subsp. multifoliolata , in contrast, contracted in future. Our results show that species-level SDMs may fail to detect climate change risks for intraspecific taxa, and consequently leading to under- or overestimation of the impacts of climate change. Incorporation of intraspecific variation into SDMs improves predictions of the impact of climate change and helps to identify appropriate conservation and management options. • SDMs that exclude intraspecific information are inadequate in Sclerocarya birrea . • Impact of climate change on subsp. multifoliolata is masked in a species-level SDM. • Intraspecific-level SDMs show robust performance than species-level SDMs. • Conservation should be based on predictions of intraspecific-level SDMs.