  Building a safety case is a common approach to make expert judgement explicit
about safety of a system. The issue of confidence in such argumentation is
still an open research field. Providing quantitative estimation of confidence
is an interesting approach to manage complexity of arguments. This paper
explores the main current approaches, and proposes a new model for quantitative
confidence estimation based on Belief Theory for its definition, and on
Bayesian Belief Networks for its propagation in safety case networks.
