Abstract: Accurately identifying and quantifying the factors influencing PM_2.5 pollution is of great significance for the prevention and control of pollution. However, the redundancy among potential factors of PM_2.5 may be overlooked. Meanwhile, the inconsistent spatial distribution of the natural and socioeconomic conditions brings unique implications for the cities within a region, which may lead to an uncertain understanding of the relationship between pollution and environmental factors. This study focused on the Beijing-Tianjin-Hebei (BTH) Region, China, which presents complex and varied background conditions. Potential impact factors on PM_2.5 were firstly screened by combining systematic cluster analysis with a random forest recursive feature elimination algorithm. Then, the representative multi-factor responsible for PM_2.5 pollution in the region during the key period of 2014–2018 (when the strict national air pollution control policy was implemented). The results showed that the key driving factors of PM_2.5 pollution in the BTH cities are different, indicating that the uniqueness of a city will have an impact on the leading causes of pollution. Further discussion shows that air control policy provides an effective way to improve air quality. This study aims to deepen the understanding of the risk drivers of air pollution within the BTH Region. In the future, it is recommended that more attention should be paid to the specific differences between the cities when formulating PM_2.5 concentration control measures.