Studying diurnal variation in the moisture con-tent of fine forest fuel (FFMC) is key to understanding for-est fire prevention. This study established models for pre-dicting the diurnal mean, maximum, and minimum FFMC in a boreal forest in China using the relationship between FFMC and meteorological variables. A spline interpola-tion function is proposed for describing diurnal variations in FFMC. After 1 day with a 1 h field measurement data testing, the results indicate that the accuracy of the sunny slope model was 100％ and 84％ when the absolute error was < 3％ and < 10％, respectively, whereas the accuracy of the shady slope model was 72％ and 76％ when the absolute error was < 3％ and < 10％, respectively. The results show that sunny slope and shady slope models can predict and describe diurnal variations in fine fuel moisture content, and provide a basis for forest fire danger prediction in boreal for-est ecosystems in China.