This paper introduces a new method for computing habitat-suitability maps without requiring absence data, called Ecological-Niche Factor Analysis (ENFA). The method is based on Hutchinson's concept of the ecological niche and uses multivariate analysis to compare the distribution of the focal species with a reference set of all cells in the study area. The first factor extracted maximizes the marginality of the focal species, defined as the ecological distance between the species optimum and the mean habitat within the reference area. The other factors maximize the specialization of the focal species, defined as the ratio of the ecological variance in mean habitat to that observed for the focal species. Eigenvectors and eigenvalues are readily interpreted and can be used to build habitat-suitability maps. This approach is recommended in situations where absence data are not available, unreliable, or meaningless. The method is illustrated and validated for the alpine ibex, a species reintroduced in Switzerland. The paper discusses the concepts of marginality and specialization, and how they relate to the ecological niche. It also describes the mathematical procedures used in ENFA, including normalization of ecogeographical variables, standardization, and factor extraction. The paper also discusses the interpretation of the factors and how they can be used to build habitat-suitability maps. The method is applied to the alpine ibex, and the results show that the species has a very restricted range of conditions they withstand. The paper concludes that ENFA is a powerful tool for drawing potential habitat maps, and that it has a wide application range, particularly for species where absence data are not available. The paper also discusses the limitations of ENFA, including its inability to handle nonlinear interactions and the need for confidence intervals on distribution maps.This paper introduces a new method for computing habitat-suitability maps without requiring absence data, called Ecological-Niche Factor Analysis (ENFA). The method is based on Hutchinson's concept of the ecological niche and uses multivariate analysis to compare the distribution of the focal species with a reference set of all cells in the study area. The first factor extracted maximizes the marginality of the focal species, defined as the ecological distance between the species optimum and the mean habitat within the reference area. The other factors maximize the specialization of the focal species, defined as the ratio of the ecological variance in mean habitat to that observed for the focal species. Eigenvectors and eigenvalues are readily interpreted and can be used to build habitat-suitability maps. This approach is recommended in situations where absence data are not available, unreliable, or meaningless. The method is illustrated and validated for the alpine ibex, a species reintroduced in Switzerland. The paper discusses the concepts of marginality and specialization, and how they relate to the ecological niche. It also describes the mathematical procedures used in ENFA, including normalization of ecogeographical variables, standardization, and factor extraction. The paper also discusses the interpretation of the factors and how they can be used to build habitat-suitability maps. The method is applied to the alpine ibex, and the results show that the species has a very restricted range of conditions they withstand. The paper concludes that ENFA is a powerful tool for drawing potential habitat maps, and that it has a wide application range, particularly for species where absence data are not available. The paper also discusses the limitations of ENFA, including its inability to handle nonlinear interactions and the need for confidence intervals on distribution maps.