Bayesian belief network models designed for specific cyber crimes can be used to quickly collect and identify suspicious data that warrants further investigation. While Bayesian belief models tailored to individual cases exist, there has been no consideration of generalized case modeling. This paper examines the generalizability of two case-specific Bayesian belief networks for use in similar cases. Although the results are not conclusive, the changes in the degrees of belief support the hypothesis that generic Bayesian network models can enhance investigations of similar cyber crimes.