AbstractClimate change and the resulting natural vegetation succession can alter vegetation productivity. However, the mechanisms underlying future productivity changes under the two influences remain unclear. Here, we used the comprehensive sequence classification system to simulate changes in global potential natural vegetation under different climate scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5), and combined the Carnegie–Ames–Stanford Approach model with random forest to assess the response of net primary productivity (NPP) to climate change and vegetation succession from 2020 to 2100. Except for SSP126, terrestrial NPP in 2100 decreased by 0.86, 2.39, and 2.54 Pg C·a−1 versus 2020 under SSP2‐4.5, SSP5‐8.5, and SSP3‐7.0, respectively. Forest was the primary contributor to terrestrial NPP changes. The total forest area was projected to increase under all scenarios, with SSP2‐4.5 showing the largest increase (358.57 × 104 km2). However, expanding forest regions exhibited a relatively low mean NPP, while stable regions demonstrated a declining pattern. Consequently, forest NPP increased under SSP1‐2.6 but decreased by 4.03, 3.43, and 0.82 Pg C·a−1 in 2100 versus 2020 under SSP5‐8.5, SSP3‐7.0, and SSP2‐4.5, respectively. In comparison, grassland and desert exerted minor influence on terrestrial NPP changes, their total NPP decreased only under the SSP1‐2.6 scenario. The grassland area decreased, but the mean NPP increased, whereas the desert area expanded, resulting in consistent changes in both total and mean NPP. Our results analyzed the effects of climate change and vegetation distribution under its influence on the change of NPP, which can deepen our understanding of their relationship.