Classification is an important step towards fingerprint recognition. In the classification stage, fingerprints are usually associated to one of the five classes “A”, “L”, “R”, “T”, “W”. The aim is to reduce the number of comparisons that are necessary for recognition. Many approaches to fingerprint classification have been proposed so far, but very few works investigated the potentialities of combining statistical and structural algorithms. In this paper, an approach to fusion of statistical and structural fingerprint classifiers is presented and experiments that show the potentialities of such fusion are reported.