Focal points refer to prominent solutions of an interaction, solutions to which agents are drawn. This paper considers how automated agents could use focal points for coordination in communication-impoverished situations. Coordination is a central theme of Distributed Artificial Intelligence. Much work in this field can be seen as a search for mechanisms that allow agents with differing knowledge and goals to coordinate their actions for mutual benefit. Additionally, one of the main assumptions of the field is that communication is expensive relative to computation. Thus, coordination techniques that minimize communication are of particular importance. Our purpose in this paper is to consider how to model the process of finding focal points from domain-independent criteria, under the assumption that agents cannot communicate with one another. We consider two alternative approaches for finding focal points, one based on decision theory, the second on step-logic. The first provides for a more natural integration of agent utilities, while the second more successfully models the difficulty of finding solutions. For both cases, we present simulations over randomly generated domains that suggest that focal points can act as an effective heuristic for coordination.