This paper discusses the framework for identifying risks in the Ultrasonic Testing (UT) of critical parts, based on the Analytic Hierarchy Process (AHP) and Bayesian Belief Network (BBN). Potential risk factors and typical Ultrasonic Testing scenarios have been investigated based on the most current literature on the subject and on a case study conducted in an aero-engine repair station. Affinity Diagram was used to categorize the risk factors. Bayesian Network combines the risk factors that contributed to an inspection failure, and AHP prioritizes the impact of risk categories. The combination of probability and impact identifies the most significant risk categories. As a result, the method can reveal the most significant risk factors in the Ultrasonic Testing of critical parts, and actions can be proposed to respond to the risks. The conclusion is that the model is adequate to significantly reduce the risk of hardware failure. As a contribution, the proposed method is an invaluable source of information for safety engineers and decision-makers in companies. It augments their knowledge and helps identify risks in UT of critical hardware and implement actions to avoid critical parts failure and improve the safety in the inspection of these parts.