We propose in this paper a model-based approach to diagnose fault situations in greatest French telecommunication networks: TRANSPAC. This approach is based on two steps: (1) Off-line step: The first step to studying faults management is to build a model. This construction is done using two abstraction levels: structural abstraction where components of the network are modeled by temporal graph and behavioral model where each component is modeled by temporal and communicating finite state machines. When the model is built, single and multiple faults are simulated in the model. Corresponding to the two level abstraction We have proposed two kind of algorithm: propagating algorithm associated to the structural level and deducting algorithm associated to the behavioral level. At the end of simulation a learning database of fault situationsis built. This database is used by discrimination module to classify given fault in the space of sequences of alarms; (2) On-line step: the expert system generated by the off-line step is used to recognize on-fly fault situations from the stream of alarms arriving at the supervisor.