Measurement specialists strive to shorten assessment time without compromising precision of scores. Computerized Adaptive Testing (CAT) has rapidly gained ground over the past decades to fulfill this goal. However, parameters for implementation of CATs need to be explored in simulations before implementation so that it can be determined whether expectations can be met. CATs can become costly if trial-and-error strategies are followed and especially if constraints are included in the algorithms, simulations can save time and money. In this study it was found that for both a multiple-choice question test and a rating scale questionnaire, simulations not only predicted outcomes for CATs very well, but also illustrated the efficiency of CATs when compared to fixed length tests.