Performance prediction modeling is a crucial step in assessing the remaining service life of pipelines. Sound infrastructure deterioration models are essential for accurately predicting future performance that, in turn, are critical tools for efficient maintenance, repair and rehabilitation decision making. The objective of this research is to develop a gravity and force main pipe performance deterioration model for predicting the remaining economic life of wastewater pipe for infrastructure asset management. For condition assessment of gravity pipes, the defect indices currently in practice, use CCTV inspection and a defect coding scale to assess the internal condition of the wastewater pipes. Unfortunately, in practice, the distress indices are unable to capture all the deterioration mechanisms and distresses on pipes to provide a comprehensive and accurate evaluation of the pipe performance. Force main pipes present a particular challenge in performance prediction modeling. The consequence of failure can be higher for the force mains relative to the gravity pipes which increases the risk associated with these assets. However, unlike gravity pipes, there are no industry standards for inspection and condition assessment for force mains. Furthermore, accessibility issues for inspections add to this challenge. Under Water Environmental and Reuse Foundation (WEandRF)'s Strategic Asset Management (SAM) Challenge, there was a planned three-phase development of this performance prediction model. Only Phases 1 and 2 were completed for gravity pipes under the SAM Challenge. Currently, 37 utilities nationally distributed have provided data and support for this research. Data standards are developed to capture the physical, operational, structural, environmental, financial, and other factors affecting the performance. These data standards were reviewed by various participating utilities and service providers for completeness and accuracy. The performance of the gravity and force main pipes are assessed with incorporating the single and combined effects of these parameters on performance. These indices assess the performance regarding; integrity, corrosion, surface wear, joint, lining, blockage, IandI, root intrusion, and capacity. These performance indices are used for the long-term prediction of performance. However, due to limitations in historical performance data, an advanced integrated method for probabilistic performance modeling to construct workable transition probabilities for predicting long-term performance has been developed. A selection process within this method chooses a suitable prediction model for a given situation in terms of available historical data. Prediction models using time and state-dependent data were developed for this prediction model for reliable long-term performance prediction. Reliability of performance assessments and long-term predictions are tested with the developed verification and validation (VeandVa) framework. VeandVa framework incorporates piloting the performance index and prediction models with artificial, field, and forensic data collected from participating utilities. The deterioration model and the supporting data was integrated with the PIPEiD (Pipeline Infrastructure Database) for effective dissemination and outreach.