To analyze the source apportionment and influence factors of heavy metals in soils surrounding a coal gangue heap in Chongqing, the absolute principal component scores-multiple linear regression （APCS-MLR） model and GeoDetector were used. The results showed that Cd was the primary pollutant and the average values of Cd, Hg, Pb, Cr, Cu, Zn, and Ni were 1.33, 0.29, 32.9, 142, 68.8, 118, and 54.6 mg·kg^-1, respectively. Using the APCS-MLR model analysis, mining sources, which were mainly affected by long-term accumulation of the coal gangue heap, had a contribution rate of 37.1% and the main heavy metal pollutants were Cd, Hg, and Pb. Agriculture and transportation sources, mainly affected by pesticide and fertilizer application and vehicle emissions, had a contribution rate of 36.2%, with the main heavy metal pollutants being Cu, Zn, and Ni. Natural sources, which were mainly affected by geotechnical weathering processes of their parent materials, had a contribution rate of 26.7% and the main heavy metal pollutant was Cr. Using GeoDetector analysis, the “distance from coal gangue heap” had the strongest explanatory power for the contents of Cd, Hg, and Pb, whereas the “distance from rural settlements” had the strongest explanatory power for the contents of Cr, Cu, Zn, and Ni. However, the interaction of each influencing factor was enhanced, which indicated that the spatial distribution characteristics of heavy metals were influenced by multiple factors. The combined application of the APCS-MLR model and GeoDetector can make the results of source apportionment and influence factors more comprehensive, accurate, and reliable.