The Beijing-Tianjin-Hebei (BTH) region of China is a typical area where both population and economy have been increasing rapidly in recent decades. The rapid economic development and population increase also bring severe environmental stresses. To better understand the factors that contribute to the regional ecological environment change, this study aims to disaggregate the effects of climate and human activity on vegetation dynamics based on a vegetation index derived from remote sensing for the BTH region through time. First, we implemented a linear regression analysis on the Enhanced Vegetation Index (EVI) in the BTH region from 2001 to 2015. We found vegetation greening mainly occurred in the mountainous area in the north and the west of the BTH region, where the forests and grasslands dominate, and the vegetation browning was mainly distributed in the southeast, where the built-up lands and croplands were located. Then, we used the Random Forest (RF) regression model to rank the importance of the climatic and anthropogenic factors. The results showed that temperature was the most influential factor among our climate variables while land cover dominated the anthropogenic variables. Finally, this study applied the RF model to disaggregate the climatic effects from that of the anthropogenic effects on vegetation dynamics by keeping human-activity- or climate-related variables constant. It showed that the method was capable of quantifying climatic and anthropogenic effects on vegetation changes. This study also found that the N deposition significantly negatively correlated with the vegetation growth trend in BTH. The approach this study proposed advanced our understanding of the driving factors of vegetation dynamics, and the approach is applicable elsewhere.