Space-borne Mie lidar is the most widely used instrument to profile aerosols in the global scale. However, due to the variation of atmospheric aerosol types, the retrieval model for aerosol extinction coefficients from lidar signals assumes a prior aerosol model, which impedes the further improvement of retrieval accuracy. As such, an iteration algorithm for aerosol extinction coefficient profiling from space-board dual-wavelength lidar observation is proposed. First, the initial extinction-to-backscatter ratio (i.e., lidar ratio) is obtained based on a prior aerosol mode and the aerosol extinction coefficient and optical depth at two channels are then retrieved. Moreover, with the relationship built between aerosol optical depth and aerosol mass column, the total aerosol mass columns at two channels are estimated. Finally, by applying the constraints that the two-channel observations correspond to the same aerosol mass column, the lidar ratio and the optical parameters are optimized iteratively based on lidar observation extensively. Due to the limitation of the channel number of the dual-wavelength lidar, the method is only applicable to the two-type mixed aerosol model. The accuracy and the applicability of the method are evaluated based on the background information of aerosol profiles in Baotou, Inner Mongolia, China. The retrieval results from the empirically estimated lidar ratio are taken as the control group. The results show that the proposed method yields mean accuracy improvement of extinction coefficient at 532 nm and 1064 nm channels by 21.16% and 3.00%, respectively. The method is also applied to CALIOP data to further validate the application potential of the proposed retrieval model.