It is investigated if a Multi Point Inflow Performance Relationship (MIPR) using Uncer- tainty Quantification (UQ) can lead to a step change in completion design. The MIPR model consists of several Kuchuk IPR models coupled with a wellbore network, and is verified against a discretized model. It is found that the assumption of artificial no-flow boundaries for this model is limiting, which leads to an overprediction of the distributed productivity index. A calibration using Markov Chain Monte Carlo (MCMC) is pre- formed, which incorporates both epistemic and aleatory model parameters. In addition, a more efficient ‘partitioned MCMC’ is investigated, which shows promising results. The UQ MIPR model can predict the change in productivity index due to a uniform com- pletion skin profile, and can give an indication of results for a non-uniform change in completion skin. In conjunction with a discretized model, a MIPR model can lead to a step change in completion by providing information to a production technologists earlier on in field development.