Urban sustainability evaluation based on indicators, is one of the practical methodologies to assess the sustainability of urban areas. In the this study the composite index used to assess the sustainability of the fourteen districts of the Isfahan metropolis. Composite index can summarize complex and multidimensional issues such as sustainability. Composite index presented in this study consist of thirteen single indices (measures) in a set of three sub-indices of ecological, social and physical environment. Based on the methodology of building composite index, after the selection of indicators, indices were normalized using the min-max method by scaling between zero and one; by using Microsoft Excel 2013 software. Then indices were weighted using factor analysis with principal component analysis method. Factor analysis for each sub-index was performed using software 22 separately and weight index was calculated based on the factor loadings. After aggregation them by a weighted linear combination, the values of ecological, social and physical sub-indices were calculated. In order to incorporate these sub-indices and making the ultimate urban sustainability composite index, the sub-index weight was calculated by using PCA / FA. The highest weight in the index is related to the ecological, physical and social sub-indices respectively. Finally, based on the weighted linear combination method, sub-indices were be aggregated and urban sustainability composite index for different areas of the Isfahan metropolis was built. This composite index indicate the quantitative sustainability value of the fourteen districts of Isfahan metropolis that can be uses to compare the sustainability of different districts of the city. According to the results, the most sustainable and unsustainable districts of Isfahan metropolis are district 1 and 10 respectively. The sustainability value of other districts indicate that there is no significant difference between these districts. Key words: Isfahan, Urban sustainability, Composite index, PCA/FA Analysis, Fourteen distric