Multi-criteria evaluation methods (MCEM) have been widely used in the scientific arena as well as in urban and regional planning. The Analytic Network Process (ANP) is one the MCEM that includes relevant tangible as well as intangible criteria and sub-criteria. It allows for a more complex relationship among the decision levels and attributes, as it does not require a strict hierarchical structure, whereas the Analytic Hierarchy Process (AHP) models a decision-making framework that assumes a unidirectional and hierarchical relationship among the decision levels. The ANP is a comprehensive technique that allows for the consideration of interdependencies among and between levels of criteria and therefore is an attractive multi-criteria decision-making tool. This feature makes ANP superior to AHP, which fails to capture interdependencies among different criteria, and sub-criteria. In other words, while AHP decomposes a problem into several levels, which contain the different elements of a decision, in such a way that they form a hierarchical structure, the ANP does not impose a strict hierarchy but rather it enables interrelationships among the decision levels and elements in a more general form by modeling the decision problem using a network structure. The network structure consists of clusters of elements, rather than elements arranged in levels. The implementation of the ANP involves the following four main steps:Step 1 – Model construction and problem structuring. This step consists of defining clearly the decision problem and structuring it into a rational system such as a network. Step 2 – Pair-wise comparisons matrices of interdependent component levels. Similar to AHP, the ANP is based on deriving ratio scale measurements founded on pair-wise comparisons among the elements and clusters of the network. Step 3 – Supermatrix formation. The supermatrix is a partitioned matrix, where each sub-matrix is composed by a set of relationships dealing with two levels in the network model. Step 4 – Prioritizing and selecting alternatives. If the alternatives are considered in the supermatrix formation, then the values in the column of alternatives of the limit supermatrix show the priority weights of alternatives. The alternative with the highest overall priority would be selected. If the alternatives are not considered in the supermatrix formation, then the selection of the best alternative is done through the calculation of a desirability index which was the case in this article. In this article the ANP is applied for site-selection of an industrial estate in a hypothetical region to show its applicability in the urban and regional setting. The results obtained show that the ANP is a powerful decision making tool in urban and regional planning which has all the advantages of the AHP, such as simplicity, flexibility and capability for utilizing quantitative as well as qualitative criteria simultaneously. Additionally, it captures both interactions and feedbacks within clusters of decision elements (inner dependence) and between clusters (outer dependence).