We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability of our information source. We contrast our approach with the success postulate in AGM-style belief revision and show how the idealizations in our approach can be relaxed by invoking Bayesian-Network models. ∗ A slightly revised version of this article appeared in V. Akman et al. (eds.), Modeling and Using Context, Berlin: Springer 2001, 421–424. 1