The paper presents a parameterized approximation scheme for probabilistic inference. The scheme, called Mini-Clustering (MC) extends the partition-based approximation offered by mini-bucket elimination, to tree de-compositions. The beneet of this extension is that all single variable beliefs are computed (approximately) at once, using a two-phase message-passing process along the cluster tree. ...