Confidence in multiphase flow predictions can influence key decisions on the design, location, and operations of pipelines and associated integrated equipment, e.g., separation systems. These decisions in turn can profoundly affect system reliability, operability, safety, and overall project economics. There may be no application where the lack of confidence in predictions is felt more strongly than for long-distance tiebacks of pipelines to subsea processing in deep water. The uncertainties and resultant confidence in simulator outputs of the flow regime, pressure drop, entrainment, and in situ velocities dictate the estimated confidence levels for opposing and complementary systems and are key contributors in a decision analysis exercise. Uncertainties in benchmarking data, input data to simulator, and internal models for various phenomena propagate to the simulator outputs of the flow regime, pressure drop, entrainment, and in situ velocities. How these discrepancies are treated will affect the scaling of the simulator to different conditions, where benchmarking data may not exist. This paper aims to raise the awareness of the importance and value of uncertainty analysis in multiphase flow systems, provide a methodology with examples, and identify some of the key gaps in the uncertainty analysis.