The R packages are used for data analysis.

<div> Bangladesh has three distinct rice-growing seasons: Aus, Aman, and Boro, each with its distinct climatic state. Climatic factors interacting with non-climatic factors impact seasonal rice yield. However, research hasn’t yet examined how climatic and non-climatic factors (CNCFs) affect the yield of rice production during the Boro season (YBR). Therefore, this study attempted to assess the impact of CNCFs on YBR using time series modeling. Accordingly, the modeling approaches used stationarity testing and pairwise correlation analysis to verify the suitability of the CNCFs for further analysis. After that, the autoregressive distributed lag (ARDL) model, the Granger causality test, and the principal component analysis (PCA) were used to predict how the CNCFs affect YBR. The ARDL model predicted that area and temperature had a substantial positive effect on YBR in both the long- and short-run, but humidity adversely influenced YBR in the long-run and positively in the short-run. The Granger causality test revealed a unidirectional causal relationship between YBR and CNCFs, except for the climatic factor rainfall. On the other hand, the non-climatic factors area, population, energy consumption, and fertilizer consumption were positively associated with YBR and substantially contributed to PC1’s (71.7%) variation. Aligning these results, this study concluded that the area, temperature, population, fertilizer consumption, and energy consumption positively impacted the YBR, while humidity negatively impacted it. These findings are crucial for ensuring Bangladesh’s rice security amid climate change, guiding policymaking, and addressing future rice demand. Therefore, policymakers and stakeholders should focus on controlling greenhouse gas emissions to keep temperatures and humidity consistent, developing climate-tolerant rice cultivars, encouraging farmers to use organic fertilizer, and adapting eco-friendly technologies for sustainable rice production. </div>