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This paper describes the application of Hybrid Intelligent Systems in a new domain: reliability of complex networks. The reliability is assessed by employing two algorithms (TREPAN and Adaptive Neuro-Fuzzy Inference Systems (ANFIS)), both belonging to the Hybrid Intelligent Systems paradigm. TREPAN is a technique to extract linguistic rules from a trained Neural Network, whereas ANFIS is a method that combines fuzzy inference systems and neural networks. In the experiment presented, the structure function of the complex network analyzed is properly emulated by training both models on a subset of possible system configurations, generated by a Monte Carlo simulation and an appropriate Evaluation Function. Both approaches are able to successfully describe the network status through a set of rules, which allows the reliability assessment [ABSTRACT FROM AUTHOR]