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To study the long-term variation in ozone (O 3 ) pollution in Sichuan Basin,the spatiaotemporal distribution of O 3 concentrations during 2017 to 2020 was analyzed using ground-level O 3 concentration data and meteorological observation data from 18 cities in the basin. The dominant meteorological factors affecting the variation in O 3 concentration were screened out,and a prediction model between meteorological factors and O 3 concentration was constructed based on a random forest model. Finally,a prediction analysis of O 3 pollution in the Sichuan Basin urban agglomeration during 2020 was carried out. The results showed that:① O 3 concentrations displayed a fluctuating trend during the period from 2017 to 2020,with a downward trend in 2019 and a rebound in 2020. ② The fluctuating trend of O 3 concentration was significantly influenced by relative humidity,daily maximum temperature,and sunshine hours,whereas wind speed,air pressure,and precipitation had less impact. The linear relationships between meteorological factors were different. Air pressure was negatively correlated with other meteorological factors,whereas the remaining meteorological factors had a positive correlation. ③ The goodness of fit statistics ( R 2 ) between the predicted and actual values of the O 3 prediction model constructed based on random forest demonstrated a strong predictive performance and ability to accurately forecast the long-term daily variations in O 3 concentration. The random forest O 3 prediction model exhibited excellent stability and generalization capability. ④ The prediction analysis of O 3 concentrations in 18 cities in the basin showed that the explanation rate of variables in the prediction model reached over 80% in all cities (except Ya'an),indicating that the random forest model predicted the trend of O 3 concentration accurately.