Many excellent papers have been written about the subject of estimating engine-out NOx on diesel engines based on real-time available data. The claimed accuracy of these models is typically around 6-10% on validation data sets with known inputs. This reported accuracy typically ignores the uncertainty around the inputs, thus arriving at an optimistic estimate of the model accuracy in a real-time application. In our paper we analyze the effect of uncertainty on the accuracy of engine-out NOx estimates via a numerical Monte Carlo simulation and show that this effect can be significant. Even though our model is based on an in-cylinder pressure sensor, this sensor is limited in its capability to reduce the effect of other measured inputs to the model. We give a brief presentation of the model and focus on the uncertainty analysis.