The Da Hinggan Mountains is one of the most important forest areas in China, but forest fire there is also of high frequency. So it is completely necessary to map forest fire risk zones in order to effectively manage and protect the forest resources. Two forest farms of Tuqiang Forest Bureau (53°34′-52°15′N,124°05′-122°18′E) were chosen as typical areas in this study. Remote sensing (RS) and Geographic Information System (GIS) play a vital role and can be used effectively to obtain and combine different forest-fire-causing factors for demarcating the forest fire risk zone map. Forest fire risk zones were described by assigning subjective weights to the classes of all the coverage layers according to their sensitivity to fire, using the ARC/INFO GIS software. Four classes of forest fire risk ranging from low to extremely high were generated automatically in ARC/INFO. The results showed that about 60.33% of the study area were predicted to be upper moderate risk zones, indicating that the forest fire management task in this area is super onerous. The RS and GIS-based forest fire risk model of the study area was found to be highly compatible with the actual fire-affected sites in 1987. Therefore the forest fire risk zone map can be used for guidance of forest fire management, and as basis for fire prevention strategies. The Da Hinggan Mountains is one of the most important forest areas in China, but forest fire there is also of high frequency. So it is completely necessary to map forest fire risk zones in order to effectively manage and protect the forest resources. Two forest farms Remote sensing (RS) and Geographic Information System (GIS) play a vital role and can be used effectively to obtain and combine different forest-fire-causing factors for demarcating the forest fire risk zone map. Forest fire risk zones were described by assigning subjective weights to the classes of all the coverage layers according to their sensitivity to fire, using the ARC / INFO GIS software. Four classes of forest fire risk ranging from low to extremely high were generated automatically in ARC / INFO. The results showed that about 60.33% of the study area were predicted to be upper moderate risk zones, indic ating that the forest fire management task in this area is super onerous. The RS and GIS-based forest fire risk model of the study area was found to be more compatible with the actual fire-affected sites in 1987. Thus the forest fire risk zone map can be used for guidance of forest fire management, and as basis for fire prevention strategies.