TAILOR is a computer program that uses the implied orders concept as the basis for computerized adaptive testing. The basic characteristics of TAILOR, which does not involve pretesting, are reviewed here and two studies of it are reported. One is a Monte Carlo simulation based on the four-parameter Birnbaum model and the other uses a matrix of children's item responses to the Stanford-Binet Intelligence Scale. In the Birnbaum model study, a variety of conditions were simulated; it was found that TAILOR typically used responses to about half the items and achieved validities with the true score within a few points of the validity of the complete test. Item discrimination parameters affected the efficiency of TAILOR. The Binet study used correlations between scores based on one bank of tailored items and another independent, parallel set and found results similar to those in the Birnbaum simulation. TAILOR, like other adaptive testing systems, apparently can aid efficiency when item discriminations are high or when ability variance is large. (Author/MV)