The Egyptian Vulture (Neophron percnopterus) is an endangered species with a globally declining population. Information on the current habitat distribution and potential suitable habitat for this ecologically important species will provide invaluable insight into conservation planning and the species’ future status as climate changes. This is specifically important for areas where there are little or no reported data on the status of the Egyptian Vulture. We used 13 years nest-site records (n = 69) together with relevant environmental variables to understand the known distribution and predict potential habitat distribution of the Egyptian Vulture in the Kurdistan Region of Iraq. A machine learning model, maximum entropy, was used to generate various model options, from which the best model was selected based on the Akaike information criterion (AICc) statistical indicators. The model showed reasonably good discriminative ability using both True Skill Statistics TSS = 0.722 and Area under the Curve (AUC) = 0.825 metrics. The Egyptian Vultures in Iraq mainly breed in territories at elevations between 1000 and 3300 m above sea level. This suggests that the species shows preference to areas distant from human settlements likely due to decreased disturbance and that the species may rely on alternative/complementary food sources (e.g. wild goat and boar). The total area of the study site is approximately 51,069 km2, out of which around 25% (12,767 km2) is predicted as suitable breeding habitat for the Egyptian Vulture. The output of this study provides useful baseline information for conservation actions and plans.