Since 2007, more than half of the world popula-tion lives in cities, causing that one of the biggest challenges of this demographic transition, which occurs mainly in developing countries since the 1970s, is providing decent housing to a growing urban population. This phenomenon, coupled with the particularities of land markets, triggers spontaneous settlements that occur in cities in an informal way and with major deficiencies in both the infrastructure and the quality of housing.Approximately one billion people worldwide live in deplorable housing conditions, lack of basic urban services and infrastructure. Most of this population lives in irregular settlements with extreme poverty within the major developing countries. The expansion of this type of settlement is considered as a visual manifestation of poverty itself. In 2000, the UN-HABITAT, organization of the United Nations, issued their ”Millennium Declaration” in which primary goals were adopted by major world leaders to improve the living conditions of the population living in informal settlements.Although irregular land occupation is a frequent occu-rrence in the cities, currently there are no reliable estimation techniques to determine its extent and characteristics reliably and expeditiously. It is from this issue, that there is a need to develop a proposal for analysis to identify and delineate the irregular settlements to an urban scale and make a diagnosis of urban infrastructure needs.This dissertation presents an alternative to identify in a timely, reliable and effective manner irregular settlements, so that different levels of government can provide quick res-ponse to regularization problems, lack of infrastructure and urban services. This research work involves the development of a model of analysis based on the integration of physical attributes, socioeconomic attributes and the spatial organization of the urban environment, using remote sensing techniques, spatial analysis and census data. These physical attributes include terrain conditions, cooperative, flood, and risk zones. Socioeconomic attributes include income levels, sewage and adaptable water coverage, overcrowding level, center- periphery relationship and land value. The attributes of spatial organization and type of building ma-terials were collected from high-resolution satellite imagery and landscape metrics. These three groups of variables were integrated into a multi-criteria model for irregular settlement identification at Ciudad Juarez, Chihuahua, Mexico with a 97.66% of accuracy. The contribution of this research is to present a new reliable method to identify irregular settlements. The achieved results can provide a great asset to help urban development officials in decision making.