For some situations the beta-binomial distribution might be used to describe the marginal distribution of test scores for a particular population of examinees. To use this distribution it is necessary to estimate two parameters which characterize the beta-binomial model. One method of estimating these parameters is to approximate the maximum likelihood estimates using some appropriately chosen iterative technique. When the number of examinees is small, however, it is not clear that this method of estimation is justified since the iterative approximations might not converge to the maximum likelihood estimate. Using Monte Carlo techniques, this paper compares the Newton-Raphson approximation to the maximum likelihood estimate with several other possible procedures. It is found that the Newton-Raphson method should be used when it yields admissible (positive) results.