[Objective] To reveal the spatial and temporal evolution characteristics of the health status of forest ecosystems in the mountainous areas of Beijing from 2005 to 2020, and to analyze the regional differences and the explanatory power of the influencing factors.[Methods] We constructed a forest ecosystem health evaluation model with “geographic environment-vegetation structure-ecological pressure-vegetation function” as the criterion layer, and applied the entropy weight-TOPSIS method to calculate the weights of the indicators and evaluate the forest ecosystem health of the mountainous regions of Beijing year by year, and analyze the characteristics of the changes in the forest ecosystem health in 2005, 2010, 2015, 2020, and the changes in the forest ecosystem health of the mountainous regions of Beijing. We analyzed the changes of forest ecosystem health in 2005, 2010, 2015 and 2020.On this basis, spatial autocorrelation analysis and K-means clustering analysis were used to explore the spatial aggregation and regional differences in ecosystem health, and the explanatory power of each indicator factor on the spatial distribution of forest ecosystem health was quantified by using the single-factor detection and interaction detection modules in Geographical detector model.[Results]:(1) From 2005 to 2020, the health level of forest ecosystems in the mountainous areas of Beijing will show an upward trend year by year.At this stage, the forest ecosystems in the mountainous areas of Beijing are mainly moderately healthy and relatively healthy, with the proportion of the area in the two areas being 41% and 48%, respectively.The spatial pattern of spatial differentiation is high in the far urban areas and low in the near urban areas. (2) The health status of forest ecosystems in the Beijing mountainous area has been improving year by year, and the change was especially obvious from 2015 to 2020, with the proportion of excellent healthy areas rising from 2.43% to 18.65%.The Moran index in the study area showed a decreasing and then increasing trend from 2005 to 2020, exhibiting significant global spatial autocorrelation and local spatial autocorrelation clustering characteristics.The spatial types of significance were dominated by positive correlation, with 41.8% and 30.8% of HH and LL types, respectively, accounting for 79.6% of the total number of significance types. (3) Soil conservation, LAI, NDVI, tree cover, and population density were the dominant factors of forest ecosystem health in the mountainous areas of Beijing, and the interactions among the factors showed nonlinear enhancement and two-factor enhancement;Forest ecosystem health in Beijing"s mountainous areas was dominated by GDP and soil retention in 2005, by LAI and soil retention in 2010-2015, and by air purification and soil retention in 2020.[Conclusions] From 2005 to 2020, the health of forest ecosystems in the mountainous areas of Beijing has continued to improve, but 27.27% of the area is still in poor or moderate ecological health, with some room for improvement. The spatial distribution of areas with poor health and low-low catchment areas is basically the same, and the construction of ecological protection and restoration projects in forest belts should be strengthened in order to safeguard the ecological health of regional forests.In future forest management and care, the enhancement and maintenance of forest ecosystem services need to be fully considered.