The risk of wildfires is increasing due to high temperatures and dry weather conditions caused by climate change. Outbreaks and spread of wildfires are usually conditioned by weather, topography, and forest stand characteristics. In the Republic of Korea (hereafter ROK), most wildfires are caused by anthropogenic factors rather than by natural factors. However, the current forest fire forecasting system being operated in ROK does not account for anthropogenic factors. To analyze the impact of human factors, along with physical factors, on wildfire occurrence, a binary logistic regression model was constructed with data for the Gangwon and Gyeongbuk provinces from January 2022 to August 2025. The dependent variable was defined as the occurrence of a wildfire, while the independent variables comprised meteorological, seasonal, stand, and anthropogenic factors. To address multicollinearity, variables with high correlation coefficients were excluded from the independent variables, which were selected by three estimating approaches including logistic regression and two machine learning techniques (namely, Random Forest and XGBoost). With machine learning, the variables with high feature importance were identified. The explanatory power of the logistic regression analysis with independent variables selected by the machine learning models was about 1.3 times higher than the model using variables adjusted solely for multicollinearity. The results of logistic regression analysis revealed that weather and coniferous forests are the most important factors fostering wildfires, while the mean stand age was the most significant factor in hindering wildfires. Among the anthropogenic factors, forest road density acted as a suppressor of wildfire spread rather than a promoter of occurrence. Conversely, trail density tends to increase the risk of wildfire occurrence. Among forest management activities, artificial forests could boost forest fires, although this remains uncertain. These findings suggest that preventing wildfires requires a paradigm shift in forest resource management policies, including extending the rotation age of forests and the conversion of coniferous forests to broadleaf forests. Meanwhile, it also indicates the need to restrict the expansion of hiking trails and improve regulations regarding hiker access to prevent wildfires.