In wildfire risk assessment, numerous factors are contributed to wildfire occurrence. And the physical model construction is complex. This paper develops a method to evaluate the wildfire risk of power transmission line corridors based on Naive Bayes Network. First, the data of 14 wildfire-related factors including anthropogenic, physiographic and meteorologic factors, are collected and analyzed. Then, the relief algorithm is used to rank the importance of factors according to their impacts on wildfire occurrence. After eliminating the least important factors in turn, an optimal wildfire risk assessment model for power transmission line corridors is constructed based on the Naive Bayes Network. Finally, this model is carried out and visualized in Guangdong Province in southern China. Then a cost function is proposed to further verify the applicability of the wildfire risk distribution map. Then a cost function is proposed to further verify the applicability of the wildfire risk distribution map. The fire-spots monitored by satellites during the first season in 2020 shows that 80.9% of fire-spots fall in higher and high risk area. This method can guide operation and maintenance personnel to carry out differentiated wildfire management work.