This study used simulation techniques to evaluate the technical adequacy of three methods for the identification of specific learning disabilities via patterns of strengths and weaknesses in cognitive processing. Latent and observed data were generated and the decision-making process of each method was applied to assess concordance in classification for specific learning disabilities between latent and observed levels. The results showed that all three methods had excellent specificity and negative predictive values, but low to moderate sensitivity and very low positive predictive values. Only a very small percentage of the population (1%-2%) met criteria for specific learning disabilities. In addition to substantial psychometric issues underlying these methods, general application did not improve the efficiency of the decision model, may not be cost effective because of low base rates, and may result in many children receiving instruction that is not optimally matched to their specific needs. (Contains 4 tables and 1 figure.)