The spatial heterogeneity of ecological vulnerability (EV) is a key indicator of regional ecosystem differentiation. However, identifying the factors that contribute to this heterogeneity remains a challenge in current research. This study proposed the “Ecological vulnerability‐spatial heterogeneity‐zone” (ESHZ) framework as a solution to overcome the difficulties of monitoring spatial heterogeneity. Then, based on the typical river valley city Baoji in Northwest China as the research object, this framework was used to analyze and predict the evolution law of heterogeneity of EV from 2000 to 2030. The findings indicate the following: (1) Synthesized ecological vulnerability index (SEVI) in 2000 and 2020 was 2.47 and 2.49, respectively, with less than 5% of the total area transitioning to areas of higher EV, indicating a relatively stable ecological environment. (2) The clustering characteristics of EV remained stable, primarily showing non‐significant, high–high, and low–low clustering, with varying degrees of heterogeneity across different regions. (3) Factors analysis revealed that DEM and LUCC had been the dominant factors of EV, and that interactions between factors were stronger than interactions within them, suggesting that its spatial heterogeneity was the result of a combination of factors. (4) The CA‐Markov model predicted a gradual improvement in the ecological environment by 2030, with a Kappa coefficient test value of 0.7733. The framework constructed in this study proposes a perspective for improved analyses of spatial heterogeneity of ecosystems, providing a viable approach to the management of regional ecological vulnerability.