Forest roads are one of the most essential structures for the continuity of timber harvesting operations. To ensure continuity, forest roads must be open and stable during all seasons. The purpose of this study is to determine the relationships between the amount of forest road reconstruction (FRR) and the factors associated with it. These include average precipitation (AP) amount, timber harvesting (industrial wood) (TH) amount and forest road repair and maintenance (FRREM) amount. Also, study aims to test appropriate statistic models for forest road planning and management. In this study, an autoregressive distributed lag (ARDL) model, which is a time series analysis method, is used. Results from the ARDL model demonstrate that an increase in the amount of TH and AP in the long-run relationship negatively affected FRR amounts. In the short-run relationship, the TH and AP variables negatively affected the FRR variable, whereas the FRREM variable positively affected the FRR variable. Granger causality test results show that in the short run there was a one-way causality from FRREM to FRR. Also, for the Granger causality test in the long run, there was causality from other variables to FRREM. This demonstrates that timber harvesting amounts and changes in precipitation amounts due to climate change should be considered when determining road reconstruction activities. In addition, this work will enable forest road managers to make effective and accurate FRR budget planning decisions.