Ticks are economically and medically important due to injuries to livestock directly caused by their bite and their ability to transmit pathogens to humans and animals. In contrast to intensively studied hard ticks, little is known about soft ticks, although these organisms, especially Ornithodoros species, transmit several pathogens, including borreliae causing tick-borne relapsing fever in humans and the virus of African swine fever affecting domestic and wild suids. As both diseases still represent a risk in Europe, we developed a model to identify suitable areas for Ornithodoros tick vectors in the Palearctic region. A GIS-based Multi-Criteria Decision Analysis was chosen due to the relative scarcity of high-quality occurrence data. Based on ecological knowledge on Palearctic Ornithodoros ticks distilled from an in-depth literature review, five criteria were identified. Two criteria were linked to critical temperatures allowing feeding activity and tick development. The three other criteria were related to the moisture availability for tick survival and development, either from precipitation, ambient humidity or other environmental factors that may provide sufficient moisture in arid zones. In order to incorporate uncertainty, a sensitivity analysis was done by performing different runs of the model and varying the environmental variables describing the respective criteria, the suitability response curves for each of the variables and the weights attributed to the different criteria for each run. Only in the final step, the available presence/absence data were used to validate the models. All models indicated suitable areas in the Mediterranean Basin and semi-desert areas in South-West and Central Asia. Most variability between the different models was observed along the edge of the highly suitable areas. The models were based on climate variables and did not aim to assess local distributions. However, it is a very useful tool to estimate the global distribution of Ornithodoros ticks and target their surveillance.