Goba woreda, despite its economical, hydrological, and biological importance both nationally and globally, the forest of the area is under serious threat owing to deforestation and forest fire. As a consequence, the forest cover of the area has been deteriorating and endemic tree species are under sever anthropogenic impacts. The aim of the present study is to determine the extent and the rate of deforestation as well as pattern of forest cover change over the past twenty seven years (1973 -2000). Besides, it also attempts to map forest fire risk susceptibility of the forest of the area using GIS and remote sensing techniques. Landsat MSS 1973 and Landsat ETM+ 2000 satellite imageries have been used to determine extent & rate of deforestation and pattern of change. Both spectral (NDVI) and post classification change detection techniques have been used to determine the forest cover change of the woreda. The forests of the area which consists of Erica bush land, moist montane forest, dry ever green forest and plantation. Among the forest classes, moist montane forest and dry ever green forests are experiencing intensive human pressure. In 1973, 62.7% (101086 ha) of the woreda was covered by forest where as the coverage dropped to 56.2 % (90603 ha) in 2000. The coverage decreased by 10.4 % within this period and it has amounted to 388.3 ha (0.2 % of the total area) deforested per year. Intensification of agricultural activities in the forest territories takes the lion share for the cause of deforestation. Seven factors such as NDVI value, vegetation type, aspect, slope, elevation and distance from settlement and roads have been taken in to consideration to examine the susceptibility of the forest to fire. The forest fire susceptibility result revealed that 35 %, 25 %, 21 % and 18 % of the forest of the woreda are categorized under the moderate, high, low and very high susceptibility level respectively. Searching fresh pasture land is the underlying cause forest fire. Key words: Deforestation, forest fire risk susceptibility, GIS, Remote sensing.