Despite advances in antifungal prophylaxis and therapy, morbidity and mortality incurred by yeasts remain a significant burden. As pathogenic yeast species vary in their susceptibilities to antifungal agents, clinical microbiology laboratories face an important challenge to identify them rapidly and accurately. Although a vast array of phenotyping and genotyping methods has been developed, these are either unable to cover the whole spectrum of potential yeast pathogens or can do this only in a rather costly or laborious way. Random amplified polymorphic DNA (RAPD) fingerprinting was repeatedly demonstrated to be a convenient tool for species identification in pathogenic yeasts. However, its wider acceptance has been limited mainly due to special expertise and software needed for analysis and comparison of the resulting banding patterns. Based on a pilot study, we demonstrate here that a simple and rapid melting curve analysis of RAPD products can provide data for identification of five of the most medically important Candida species. We have termed this new approach melting curve of random amplified polymorphic DNA (McRAPD) to emphasize its rapidity and potential for automation, highly desirable features for a routine laboratory test.