It is of great significance to reveal the spatiotemporal pattern of PM_2.5 pollution in North China Plain (NCP), and relative importance of influencing factors for controlling PM_2.5 pollution in NCP. In this work, statistical models between PM_2.5 and a set of influential factors were firstly established to pinpoint the dominant factors contributing to PM_2.5 variations in NCP and to estimate the daily PM_2.5 dataset. The results of model attribution analysis showed that emission factors such as NO₂ and SO₂ were the two dominant influencing factors of PM_2.5 pollution in NCP, while temperature, relative humidity and wind speed were three main meteorological factors that significantly contributed to PM_2.5 pollution. Subsequently, spatiotemporal analysis results showed that there was obvious spatial agglomeration of PM_2.5 pollution in NCP, and the most serious PM_2.5 pollution occurred at Beijing and the junction of Hebei, Shanxi and Henan. Meanwhile, PM_2.5 pollution has a strong seasonal pattern, and the highest pollution is in winter while the lowest is in summer. In addition, PM_2.5 pollution level in NCP showed a downward trend from 2015 to 2020. Among them, the most serious PM_2.5 pollution in 2020 decreased most significantly, which was 71.52 % lower than that of 2019.