Abstract The 13 C‐urea breath test (UBT) is currently regarded as one of the most important noninvasive diagnostic methods for detecting Helicobacter pylori ( H. pylori ) infection in adults and children. However, for infants and young children, the standard for UBT interpretation has not been validated, and its reliability has not been established for diagnosing H. pylori infection in this group. The primary outcome data from UBT consist of mixture data, which come from subjects whose H. pylori infection classifications are unconfirmed. In this paper, we propose the finite mixture distribution method to identify a reliable UBT cut‐off value in a large baseline sample in which gastric biopsy is not available to confirm the H. pylori infection in younger children. Maximum likelihood estimators of the parameters in the mixture model were obtained using an expectation maximization (EM) algorithm. The standard deviation of the cut‐off point was estimated by bootstrap methods. We applied the same analytical methods to the UBT results yielded from the follow up, as well as the overall UBT results in the longitudinal cohort data. The cut‐off points from those UBT data sets are similar. The advantage of the finite mixture model is that it may be used to calculate sensitivity and specificity in the absence of other diagnostic tests. Copyright © 2004 John Wiley & Sons, Ltd.