The present study investigated a recently developed automated image analysis technique for its applicability to the enumeration of selected bacteria in supragingival dental plaque. Following initial calibration, the system is capable to count fluorescence-labeled target cells in up to 48 samples without user interference. Test samples contained a characteristic mixture of planktonic bacteria, small almost planar bacterial aggregates, and large, virtually indisruptable clumps with cells from multiple species. Due to their complex composition, these samples provided a challenging validation step for the image analysis system. Automated enumeration of target bacteria was compared with visual counting of the fluorescence-labeled bacteria. Results are shown for six taxa (Actinomyces naeslundii, Fusobacterium nucleatum, Prevotella intermedia/Prev. nigrescens, Streptococcus gordonii/Strep. oralis/Strep. sanguis, Strep. sobrinus, and Veillonella dispar/ V. parvula) with characteristic differences in abundance, cell morphology and aggregation behavior. Results revealed good correspondence between the two enumeration techniques (correlation coefficients ranging from 0.77 to 0.92) provided that the portion of target bacteria exceeded 0.05% of the total bacterial cell number. This work demonstrates the applicability and usefulness of fully automated immunofluorescence to analyze such complex ecosystems as supragingival dental plaque.