A multilevel Bayesian approach is proposed for damage assessment in layered materials. The method does not require any predefined hypothesis about damage distribution. Several damage hypotheses are tested and ranked through relative probabilities. A case study is presented using through-transmission ultrasonic data in a CFRP laminate. The method enforces a quantitative Ockham's razor for damage hypothesis selection.