In case classification in a limited number of categories is the main purpose of testing, computerized adaptive tests (cats) in which algorithms are based on the application of sequential statistical testing have shown to be better performing alternatives above traditional estimation based cats. See, e.g. Reckase, (1983) and Eggen & Straetmans, (2000). In these algorithms the Sequential Probability Ratio Test (SPRT) (Wald, 1947) is applied in order to decide on whether more observations on items are needed and on which classification decision is to be taken. When a decision cannot be taken with the predetermined decision error rates, in practice the procedure is always truncated at a maximum test length. If the Rasch model is used as the item response model for the available item bank applying the SPRT is very elegant and simple. In the paper the procedures will be explained. The performance of the SPRT based cats with the Rasch model will be illustrated with results of simulation studies with an existing item bank. The item bank that will be used is the bank developed in ESMaG project for measuring mathematics ability for the primary school in Germany