Forest-cover dynamics is of wide concern due to its role in climate change, biodiversity losses, water balance and land degradation, as well as social and economic development. Hence, exploring land-use/cover dynamic is important in order to improve our understanding of the causes of forest-cover change and to detect the future trend. Furthermore, projecting a future land-use/cover pattern can help identifying potential areas where forest-cover change will occur in the future and the potential consequences of these processes in order to improve land-use planning and policies. Similar to other East European countries, Romania is experiencing rapid land-use/cover changes after the breakdown of socialism; a clear trend was registered by deforestation, which reflects the consequences of a continuous forests dynamics and little environmental care. Consequently, this study, carried out in order to analyse the potential future cover-change, resulted in the land-use/cover scenario (2007–2050) simulated using CLUE-S (the Conversion of Land Use and its Effects at Small regional extent) modelling framework, applied to development regions in Romania. Overall, the model results in different spatial patterns of land-use/cover change, projecting a slight increase in the forest-cover area of about 82,000 ha. Furthermore, the model simulated widespread deforestation, mainly in relation to agricultural land expansion. The area under the curve (AUC) for the relative operating characteristic (ROC) and the Kappa simulation (KSimulation) were used to assess the predictive power of the determinant factors included and to evaluate the spatial performance of the model. The obtained ROC/AUC values (0.83–0.88) indicate the great power of the determinant factors to explain the forest-cover pattern in the area. Furthermore, the KSimulation scores (0.69–0.79) highlight the potential of the CLUE-S model to simulate future forest-cover change in relation to the other land-use/cover categories. The results can provide useful inputs for effective forest resource management and environmental policies. Moreover, the spatial data obtained can contribute to exploring future potential environmental implications (e.g. assessing landslide and flood hazard scenarios, forest biomass dynamics and their impact on carbon allocation, or the impact of forest-cover change on ecosystem services).