The Middle East region, with its semi-arid and arid climate and position adjacent to the vast deserts, is highly prone to land degradation and dust storms. Land-use changes and urbanization over the last decades have added extra pressure on the environment at an ever-increasing pace. This study aimed to simulate future land-use changes for 2040, 2070, and 2100 using the CA-Markov model and to evaluate their impact on dust storm occurrence. Dust Storm Sensitivity Mapping (DSM) was conducted using three machine-learning models) BA, XGB, and CA) based on 1634 dust occurrence points and nine environmental factors. Validation results indicated that the BA model had better performance than the other models, with SPF = 83.55 % and AUC = 0.821. Statistical tests (Friedman and Wilcoxon) confirmed the existence of significant differences between the performances of models at the 95 % CI. Land use simulations project a substantial increase in barren lands and areas with no vegetation between 2040-2070 and 2070-2100, mainly caused by unsustainable land management, overgrazing, deforestation, and inefficient agricultural practices, which results in soil degradation and reduced capacity for vegetation cover. Further, urban expansion and population growth were determined to accelerate the degradation of agricultural plots. Sensitivity maps confirmed that significant parts of the Middle East lie in high to very high dust hazard zones, triggered by geomorphological factors, climatic change, socioeconomic pressures, and geopolitical tensions. Integration with machine-learning models accomplished high accuracy in DSM, offering reliable tools for regional planning. The study highlights that if there is no proper land management, future land-use patterns will significantly increase dust storm events. This study provides policymakers and planners with valuable insights for implementing sustainable land-use strategies and targeted mitigation measures to reduce dust-related hazards in the region.