In this study, the central deflection monitoring of the Baishihu Suspension Bridge in Neihu District, Taipei City was used as the research object. Based on 109 monthly monitoring data in the past, 104 of them were analyzed and predicted using statsmodels using Python for time series analysis and prediction. The five data was used for verification and time series decomposition. The methods include CLASSICAL DECOMPOSITION classic decomposition (addition and multiplication model) and STL DECOMPOSITION decomposition for analysis, and then use simple moving average (SMA) prediction, weighted moving average (WMA), exponential moving average (EMA), STL for prediction ( EMA) makes predictions, and discusses and recommends the results of analysis and prediction.