As a critical ecological barrier, the three northeastern provinces of China have profound ecological significance. The distinctive distribution patterns of vegetation, shaped by specific geographical endowments and climatic regimes, have a unique position among global environmental change research. This study aims to characterize future climate change and vegetation dynamics in response to global warming development, and to reveal the mechanistic responses of future vegetation change to extreme climate changes. In this study, we employed a multiple linear regression model to quantify the spatiotemporal correlations between NDVI and climatic variables (temperature/precipitation), based on high-resolution meteorological datasets and Normalized Difference Vegetation Index (NDVI) time-series (2001-2020). Then we used a univariate linear regression model combined with the Theil-Sen estimator and Mann-Kendall (M-K) test to study vegetation changes under different Shared Socioeconomic Pathways (SSPs245and SSPs585). The results show as follows: (1) Under the SSP245 and SSP585 climate scenarios, an overall fluctuating upward trend in temperature and precipitation was observed in the three northeastern provinces of China. (2) Under the SSP245 and SSP585 scenarios, NDVI shows a fluctuating decrease and a fluctuating increase, respectively. Spatial heterogeneity was evident in the vegetation distribution pattern. (3) Temperature and precipitation influence vegetation distribution, and NDVI also responds to climatic variation. These findings provide a scientific basis for evidence-based climate adaptation strategies and sustainable ecosystem management in Northeast China.