‘Classic MaxEnt’ is a Bayesian derivation of the MaxEnt treatment of inverse problems leading to a posterior probability ‘bubble’ over the solution. This probability bubble—which is maximised at the optimal regularised solution—provides the framework for quantitative inferences about the solution. In particular, the framework allows the computation of fluxes and associated error bars over the solution. This is an important advance in the general theory of inverse problems which has thus far lacked a quantitative reliability treatment of the computed solution. This paper discusses this quantification procedure and applies it to practical NMR spectroscopy.