For fire safety studies in nuclear facilities, IRSN uses the SYLVIA software to simulate fire scenarios in highly confined and mechanically ventilated compartments, and airborne contamination transfers inside nuclear facilities. In order to take into account the different sources of uncertainty coming from initial and boundary conditions as well as from model parameters, the SYLVIA software is associated with the SUNSET statistical software. However, such a use of SYLVIA requires a large number of runs and a significant statistical analysis, what is not always compatible with the requirements of safety assessments in terms of deadlines. To overcome this difficulty, IRSN is currently developing expert systems based on SYLVIA databases. This approach allows deriving the most likely diagnosis or prognosis in a very short time, but also deriving a more complex form of reasoning intertwining prognostic and diagnostic inferences. These expert systems are based on the Bayesian Belief Network methodology and consist in two steps: first, a large database obtained from SYLVIA runs allows the estimation of conditional probability tables. Then, a message passing algorithm is used to exploit dynamically this database. The illustrating example is based on the study of pressure effects due to fire in nuclear facilities. The database is made up of 1,600,000 runs of the SYLVIA software. It shows how an expert system can be used as a decision support tool for fire safety analysis in nuclear area. The development of expert systems represents a new generation of computational tools in the field of probabilistic fire simulation.