ASCAL is a microcomputer-based program for calibrating items according to the three-parameter logistic model of item response theory. It uses a modified multivariate Newton-Raphson procedure for estimating item parameters. This study evaluated this procedure using Monte Carlo Simulation Techniques. The current version of ASCAL was then compared to the current version of LOGIST and a prior version of ASCAL that was used to estimate the parameters in the adaptive item pool of the Armed Services Vocational Aptitude Battery. Parameters were estimated for the items in each of three different-simulated tests. Three different evaluative criteria were used: (1) root mean squared error between true and estimated item parameters, (2) the correlation between true and estimated item parameters, and (3) calibration efficiency. Results suggest that ASCAL produces parameter estimates that are at least as accurate as those produced by LOGIST. There were only minor differences in the three evaluative criteria between the two versions of ASCAL. The differences between ASCAL and LOGIST were slightly larger than the differences between the two versions of ASCAL. Item parameter error increased markedly according to all three criteria and for all calibration procedures when items with an exaggerated range of difficulty parameters were calibrated. (Author/JAZ)