Urban agglomeration is the major form of China's new urbanization, which has greatly advanced national economic development. However, rapid regional urbanization has posed serious pressures on ecosystems, and it restricts the sustainable development of cities. We studied the Beijing-Tianjin-Hebei Metropolitan Region (BTH), which is undergoing rapid urbanization but is also facing many ecological environmental problems, as a case example to analyze the dynamics of landscape change and their driving factors during 1990-2010. To do this, we used the logistic model and simulated changes in land-cover by using the CLUE-S model. Then, we predicted the changing trends of the landscape patterns of BTH in 2020. The results were as follows:(1) there was a marked change in the landscape patterns of BTH during 1990-2010. The proportion of the artificial surface clearly continued to increase, whereas that of the cultivated land significantly decreased. The spatial configurations of forest land and grassland showed obvious temporal changes; (2) The major drivers of land-cover changes of BTH included both topographic and social-economic factors. Moreover, for different landscape types, the driving dynamics varied. For instance, the forested lands were more likely to occur northeast of BTH at high elevation and steep slopes while the water body, artificial surface and other landscape types were more likely to occur in plains and low-lying areas. The driving forces of landscape change also changed temporally. An example of this is how the distribution of artificial surface changed from being close to the central area in 1990-2000 to being away from the center, thus closer to railways and highways; (3) The CLUE-S model was robust in its application for the simulations of land-use dynamic changes of BTH, and the kappa index was 0.84. By 2020, the artificial surface of BTH was predicted to increase whereas cultivated land would continue to decrease. The most stark changes in landscape patterns should occur in core cites such as Beijing, Tianjin, Tangshan, and Shijiazhuang.