With the rapid socioeconomic development in China, the competition for space in land-use conversion is getting fierce. The Wuhan metropolitan area, as one of the main areas of modern agriculture and manufacturing, has been significantly affected by urbanization, industrialization, and national development policies, resulting in regional man-land contradiction. In this complex region, scientifically measuring the land-use/land-cover (LULC) dynamics and exploring the spatiotemporal evolution characteristics of the LULC changes are important tasks for local officials and decision makers in the management of urban expansion and land-use planning. In this study, an integrated logistic multi-criteria evaluation (MCE) cellular automata (CA) Markov (logistic-MCE-CA-Markov) model and a geographic information system (GIS) were used to evaluate and predict the LULC changes. The analysis was based on six LULC maps at equal temporal intervals derived from land-use data for 1990, 1995, 2000, 2005, 2010, and 2015, along with topographic spatial layers (elevation and slope) derived from an ASTER digital elevation model. In addition, other spatial variables (points of interest, gross domestic product(GDP), population density, proximity to urban center, and proximity to transportation line) were incorporated in the simulation process. The simulated results obtained by the integrated logistic-MCE-CA-Markov model had a kappa coefficient of 88.582% and a figure of merit value of 27.935%. The results indicated that, under the influence of the various factors, the future land-use pattern of the Wuhan metropolitan area will be clearly transformed. From 2015 to 2025, it is predicted that the area of arable land and woodland will decrease by 1506.152 km2 and 1743.945 km2, respectively, and urban land expansion will mainly come from arable land, woodland, and other construction land. With the enhancement of the human disturbance intensity, the natural landscape patches will become segmented, and the number of individual patches will increase gradually, enhancing the spatial heterogeneity. The simulation results could not only be used to monitor future LULC trends, but could also help local decision makers to provide policy support for land-use planning and management.