We present a full Bayesian method for estimating the density and size distribution of subclad-flaws in French Pressurized Water Reactor (PWR) vessels. This model takes into account in service inspection (ISI) data, a flaw size-dependent probability of detection function (different function types are possible) with a threshold of detection, and a flaw sizing error distribution (different distribution types are possible). It is identified through a Markov Chain Monte Carlo (MCMC) algorithm. The article includes discussion for choosing the prior distribution parameters and an illustrative application is presented highlighting its ability to provide good parameter estimates even when a small number of flaws is observed.