[Objective] The ecological product values(EPV) were evaluated and the driving factors of their spatial change were also explored in Hebei Province, which is to provide a scientific foundation for establishing an ecological security barrier in the Beijing-Tianjin-Hebei region while expediting ecological civilization development.[Methods] The EPV were computed for 168 counties in Hebei Province during 2010, 2015, and 2020 by use of the equivalent factor method. Spatial distribution evolution and clustering characteristics were analyzed utilizing the global Moran index, high/low clustering index, and the hotspot analysis method. Geographic detector was employed to identify the primary driving forces. [Results] ① Between 2010 and 2020, Hebei Province's EPV surpassed 380 billion yuan, exhibiting notable overall improvement. EPV exhibited a pattern of gradual increase followed by rapid growth, exceeding 420 billion yuan by 2020. Forest land had the highest EPV, consistently dominating the ecological product types Water areas had the next highest EPV, and experienced the most substantial changes in both amount and rate. ② During 2010 to 2015, EPV's spatial distribution exhibited a north-south and west-east dichotomy, with high values concentrated in the northern Yanshan and Bashang Plateau regions, as well as in the western Taihang Mountain area, while lower values clustered in the southeastern Hebei Plain. During 2015 to 2020, the north-south divide persisted, with added east-west variation and central low values. ③ From 2010 to 2020, significant high-value clustering was observed spatially, mirroring the distribution pattern of cold and hot spots. ④ Single-factor analysis identified CO surface concentration, O3 concentration, and average annual temperature as primary influencers of EPV's spatial evolution. Per capita GDP emerged as the secondary vital factor, while the impact of social factors remained comparatively weak. Dual-factor interaction analysis revealed that the leading combinations of factors during the three periods were per capita GDP ∩ NO2 surface concentration, elevation ∩ O3 concentration, and per capita GDP ∩ CO surface concentration, with corresponding q values of 0.71, 0.73, and 0.66, respectively. [Conclusion] While forest land and water areas hold pivotal roles in augmenting EPV, significant spatial disparities exist. To drive more positive transformations, it is essential to not only consider robust ecological single-factor drivers, but also to comprehensively grasp the intricate and nonlinear nature of driving force origins.