Dust storms (DSs) are among the major environmental problems. Deprived of coherent and scientifically acceptable policies, most governments have failed to manage effectively this recurring phenomenon. Currently, many organizations aim to enhance the resilience of communities and manage hazards such as dust through educational measures. The present study investigated the farmers’ resilience and the factors reducing their vulnerability to DS events. To this end, a mixed-methods research approach was employed. This approach includes applying the Grounded Theory and Survey methods in the qualitative and quantitative phases. Qualitative findings were analyzed using Atlas. ti 9 software and the factors affecting farmers’ resilience to dust were extracted at the end of the qualitative phase. Meanwhile, the model of the factors affecting the increased level of resilience and the effect of resilience in reducing the vulnerability of farmers to dust were extracted in the quantitative phase. The model was designed and validated using structural equation modeling (SEM) through the partial least squares (PLS) method in the SmartPLS3 software. The findings of the qualitative phase demonstrated that the factors affecting farmers’ resilience to dust include economic, education extension, and support factors. In the quantitative phase, modeling results revealed that assets and access to basic services (ABS) were among the important dimensions of resilience. Furthermore, educational and extension factors had a significant positive effect on increasing resilience and reducing vulnerability.