Forward feeding uncertainty analysis makes no comparison against any measured data. It assumes that all the approximations made are correct or negligible and that the methodology and model are valid/reasonable representatives of the real physical system. This assumption may be based on past performance within different set-ups or the hypothesis that the system is physically correctly represented. The arguments made earlier do question the fundamental possibility of such assumptions. Therefore, such analyses should be associated with a caveat that the results are conditional on the uncertainties assumed a priori. However, the methodology is vital in the model development phase as well as in conditions in which no or not enough measurements can be acquired. Moreover, in situation in reliability problems of unobserved or unrepeatable events it is the only alternative (see discussion in Hall and Anderson (2002). However, model evaluation and conditioning should be carried out to check model predictions whenever the observations are available.