This paper proposes a framework for distributed network management by incorporating fault and performance management metrics in a hierarchical decision making model. The goal of this research is to automate the fault management process. The fault management system is organized as a three level information processing model. Correlation results from each level are provided as evidence to the next level. Causal and temporal relationships between monitored variables are captured using Dynamic Bayesian Networks. As evidence is gathered, the probability of the presence of a fault is either strengthened or weakened. The proposed model is used for proactive fault detection as well as fault isolation purposes. A prototype implementing the ideas is presented.