Expert systems can be used to aid decisionmaking. A computerized adaptive test is one kind of expert system, although not commonly recognized as such. A new approach, termed EXSPRT, was devised that combines expert systems reasoning and sequential probability ratio test stopping rules. Two versions of EXSPRT were developed, one with random selection of items (EXSPRT-R) and one with intelligent selection (EXSPRT-I). Two empirical studies were conducted in which these two new methods were compared to the traditional SPRT and to an adaptive mastery testing (AMT) approach based on item response theory (IRT). The EXSPRT-I tended to be more efficient than the AMT, EXSPRT-R, and SPRT models in terms of average test lengths. Although further research is needed, the EXSPRT-I initially appears to be a strong alternative to both IRT- and SPRT-based adaptive testing when categorical decisions about examinees are desired. The EXSPRT-I is clearly less complex than IRT, both conceptually and mathematically. It also appears to require many fewer examinees to establish empirically a rule base when compared to the large numbers needed to eliminate parameters for item response functions in the IRT model. (20 references) (Author/BBM)