Abstract: Based on the pollen data of Fenzhuang profile from the Late Pleistocene to the Early Holocene, the paper gives a further analysis to subdivide zones of pollen assemblages and changes of paleovegetation and paleoenvironment in this area using principal component analysis (PCA). In the paper 11 pollen types were selected from original records of 54 samples in the profile, then 54?11 matrix was set up. The first factor of PCA indicates the development process intensity of herbs and cold trees, on the contrary, the development process intensities of in Tila and Pinus and ferns (Selaginella sinensis, Polypodium) were restrained. The second factor of PCA indicates the development process intensity of mesophytic herbs and Artemisia+Compositae. In the meantime the development of aquatic plants and hydrophe may be restrained. The third factor of PCA indicates the co development of aquatic plants and mesophytic herbs in Beijing region. From the scatter diagrams of 1,2 and 1,3 factors, 54 pollen samples were divided into 4 types (correspond to 4 zones). In type A (zone 1, over 13000 a B.P.), the vegetation was steppe dominated by Artemisia and Chenopodium, the climate was dry and cold. In type B (zone 2, ca. 13000 a B.P.-11400 a B.P.), the vegetation was dominated by a subalpine conifer forest, aquatic plants increased, the climate was cold and wet. In type C (zone 3, ca 11400-11000 a B.P.), the vegetation was represented by temperate broadleaf tree such as Tilia, the aquatic plant was predominant too, lakes and swamps deceased, the climate was warm and became dry. In types D (zone 4), since 11000 a B.P. trees and aquatic plants developed better at its initial stage, but afterwards they obviously reduced after 10000 a B.P., with subdividing zone of Fenzhuang profile, there were differences in the third zone between Kong and Liu, the reason is that the C type is transitional. Finally the biodiversity in plant communities and complex geographical environment in Beijing area, using great dispersal of accumulative percent of total in PCA, may sufficiently echo this character, for cumulative only 57% from the first three factors.