Condition assessment of oil and gas pipelines is a significant component in pipeline operations and maintenance. Such assessments are used to ensure better decisions for repair and/or replacement to reduce pipelines' failure possibilities. Therefore, it is essential to have an effective condition assessment model for pipelines as their failure incidents may lead to catastrophic economical and environmental consequences. Current practices of assessing gas pipelines condition can be considered simplified for the intended purpose. They mainly depend on experts' opinions in interpreting inspection data. This process is influenced by the human subjectivity and reasoning uncertainty. To address the weaknesses of the current practices, this book proposes a new fuzzy-based methodology that utilizes integrated analytic network process (ANP) and hierarchical evidential reasoning (HER) to develop a meticulous condition assessment model for offshore gas pipelines. The proposed model is validated using historical inspection reports that are obtained from a local pipeline operator in Qatar. After validation , the model is found to deliver satisfactory outcomes in assessing pipelines condition.