Benthic habitat mapping is a rapidly growing field of underwater remote sensing studies. This study provides the first insight for high-resolution hydroacoustic surveys in the Slupsk Bank Natura 2000 site, one of the most valuable sites in the Polish Exclusive Zone of the Southern Baltic. This study developed a quick and transparent, automatic classification workflow based on multibeam echosounder and side-scan sonar surveys to classify benthic habitats in eight study sites within the Slupsk Bank. Different predictor variables, four supervised classifiers, and the generalisation approach, improving the accuracy of the developed model were evaluated. The results suggested a very high significance for the classification performance of specific geomorphometric features that were not used in benthic habitat mapping before. These include, e.g., Fuzzy Landform Element Classification, Multiresolution Index of the Valley Bottom Flatness, and Multiresolution Index of the Ridge Top Flatness. Comparison of classification results with manual maps demonstrated that Random Forest had the highest performance of four tested supervised classifiers. Because the current needs include benthic habitat mapping for the whole area of the Polish Exclusive Economic Zone, the key findings of this study may be further applied to extensive areas in the Polish waters and other vast areas worldwide.