With the rapid development of industrialization and urbanization, atmospheric pollution research is vital for regional sustainable development and related policies formulated by the government. Previous studies have mainly studied a single evaluation method to analyze the air quality index (AQI) or single air pollutant. This research integrated the Spearman coefficient (SC) correlation analysis, a random search (RS) algorithm and an excellent extreme gradient boosting (XGBoost) algorithm to evaluate the air pollution influence of industrialization and urbanization (APIIU). Industrialization, urbanization and meteorological indicators were used to measure the influence degree of APIIU on AQI and particulate matter 2.5 (PM_2.5), respectively. The main findings were: (1) the APIIU-AQI and APIIU-PM_2.5 of Henan Province, Hubei Province and Hunan Province had significant changes from 2017 to 2019; (2) the value of square of determination coefficient of real value (R²), the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of APIIU-AQI and APIIU-PM_2.5 in three provinces predicted by the SC-RS-XGBoost were 0.945, 0.103, 4.25% and 0.897, 0.205, 4.84%, respectively; (3) the predicted results were more accurate than using a SC-XGBoost, RS-XGBoost, traditional XGBoost, support vector regression (SVR) and extreme learning machine (ELM).