In this article, sequential meta-analysis is presented as a method to determine the sufficiency of cumulative knowledge in single-case research synthesis. Sufficiency addresses the question whether there is enough cumulative knowledge on a topic to yield convincing statistical evidence. The method combines cumulative meta-analysis of single-case experimental data with formal sequential testing. After describing the underlying statistical techniques, a strategy to conduct a sequential single-case meta-analysis is illustrated using a real meta-analytic database. The sequential methodology may serve as a valuable tool for behavioral researchers to guide them in making optimal use of limited resources.