The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the validity of the proposed method in both measurement precision and classification accuracy. The results indicate that the MST test information effectively predicted the performance of MST. In addition, the results of the current study highlighted the relationship among the test construction, MST design factors, and MST performance.