An explanation facility is an important component of an expert system, but current systems for the most part have neglected the importance of tailoring a system's explanations to the user. This paper explores the role of user modeling in generating expert system explanations, making the claim that individualized user models are essential to produce good explanations when the system users vary in their knowledge of the domain, or in their goals, plans, and preferences. To make this argument, a characterization of explanation, and good explanation is made, leading to a presentation of how knowledge about the user affects the various aspects of a good explanation. Individualized user models are not only important, it is practical to obtain them. A method for acquiring a model of the user's beliefs implicitly by "eavesdropping" on the interaction between user and system is presented, along with examples of how this information can be used to tailor an explanation.