We present a mechanism for remembering explanations and re-using them to explain newepisodes. This task requires a representation scheme for explanations, a dynamically organizedmemory, and a means of modifying old explanations to fit new facts. In this paper we focus onmemory organization. W e describe strategies for indexing and retrieving explanations, for usingcausal knowledge to select relevant features of episodes and for guiding generalization. W e discusswork in progress on a computer implementation of this model.