Retrieving information from memory enhances long-term retention. In this manuscript, we describe the dual-memory framework, which makes interval-scale predictions of the magnitude of this retrieval practice effect. After outlining the framework, we use data from our laboratory-both at the group level and at the distribution level-to fit the equations from the dual-memory framework. Overall, we successfully fitted the model predictions to the observed average data. In addition, we compared the predicted and the observed distributions of performance in the retrieval practice condition. More importantly, we introduce a useful approach to simulate empirical scenarios and test the relationship between individual-difference variables and the retrieval practice effect. We illustrate the application of this approach using data from a study that measured fluid intelligence. Future studies may benefit from contrasting different strength-based frameworks.