This paper presents an application of Bayesian Belief Networks for modeling the uncertainty in aircraft safety diagnostics. Belief networks or influence diagrams represent possible means to efficiently model uncertain causal relationships among components of a system. HUGIN is a software for the construction of knowledge based systems based on Bayesian networks. A HUGIN prototype is dicussed to illustrate how a Bayesian approach could be used to support the decision search routine of aircraft safety inspectors when diagnosing equipment of subsystem malfunctions. The example focuses on diagnostic procedures for assessing aircraft tire condition.