Conventional biometric identification systems require exhaustive 1 : N comparisons in order to identify a bio- metric probe, i.e. comparison time frequently dominates the overall computational workload. Biometric database indexing represents a challenging task since biometric data does not exhibit any natural sorting order. In this paper we present a preliminary study on the feasibility of applying Bloom filters for the purpose of iris biometric database indexing. It is shown that, by constructing a binary tree data structure of Bloom filters extracted from binary iris biometric templates (iris-codes), the search space can be reduced to O(log N ). In experiments, which are carried out on a medium-sized database of N = 256 subjects, biometric performance (accuracy) is maintained for different conventional identification systems. Further, perspectives on how to employ the proposed scheme on large-scale databases are given.