Forest biomass is very important in the study of carbon cycle at the earth’s surface, and hence its accurate estimation has great significance for the problem of the global and even regional forest conditions and climate environments. Due to its unique imaging mechanism, all-weather all day long properties and penetration capability of the forest canopy, synthetic aperture radar (SAR) plays an enormous role in forest resources management and forest mapping research. This paper first summarizes the traditional forest biomass estimation methods in the forestry and the methods based on the optical remote sensing data and LiDAR data, and then deals with the forest biomass inversion methods from such angles as SAR backscatter (different polarization mode), interference coherence, and polarization interference. The advances and development trend for forest biomass estimation based on SAR are also summed up in this paper.