The urban sewer pipeline network is a vital urban infrastructure that is highly at risk of failure and its deterioration can be harmful to the environment and public health and safety. Therefore, for performing an effective rehabilitation program, it is needed to prioritize the sewer pipelines. In this paper, a novel risk assessment approach is proposed for prioritizing sewer pipelines based on a combination of Geospatial Information System (GIS) and Analytic Hierarchy Process (AHP)- Data Envelopment Analysis (DEA). To do so, it calculates the Probability of Failure (PoF), along with the Consequence of Failure (CoF) for the sewer pipelines. Bayesian Network (BN) as the probabilistic method is used to calculate PoF. The main contribution of the study lies in using a combination of GIS, AHP, and DEA for quantitatively assessing the CoF, firstly, the criteria weights are determined by the AHP method through experts' judgments. Then, GIS functionalities along with DEA, are used to calculate scores for the alternatives. Finally, the outputs of the AHP method are integrated with the outputs of the DEA method in order to calculate CoF. The proposed method is applied to a local sewer pipeline network as a real-world case study to assess its risk of failure. The results indicated that the sewer pipelines are in good condition in the study area and among 1605 sewer pipelines, only 48 of them (about 3 %) are in a critical situation that it is needed to perform rehabilitation program. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.