  This paper aims to motivate Bell's notion of local causality by means of
Bayesian networks. In a locally causal theory any superluminal correlation
should be screened off by atomic events localized in any so-called
\textit{shielder-off region} in the past of one of the correlating events. In a
Bayesian network any correlation between non-descendant random variables are
screened off by any so-called \textit{d-separating set} of variables. We will
argue that the shielder-off regions in the definition of local causality
conform in a well defined sense to the d-separating sets in Bayesian networks.
