The importance of marinas as infrastructures for recreational boating is increasing substantially. However, information on their soft-bottom benthic communities, a key tool for managing programmes, is still scarce. We combined environment features with macro- and meiofaunal soft-bottom community information for assessing the ecological status of marinas with an integrative approach. To address this issue, we focused on eight marinas of the Southern Iberian Peninsula. Macro- and meiofauna data revealed high benthic heterogeneity at a spatial scale. The environmental variables which correlated best with macrofauna were mainly phosphorus, granulometry, and total organic carbon, and secondarily important variables were faecal coliforms, the biocide Irgarol, and heavy metals; total hydrocarbon concentration was also significant for meiofauna. Annelida was the dominant phylum in terms of number of species (37%) and abundance (66%) and were better descriptors of the environmental conditions than Arthropoda and Mollusca. Although identification to the species level is desirable and mandatory for assessing biological pollution, significant differences among marinas and correlations between fauna and abiotic variables were already detected at the level of family and order. This implies that biota assessment at higher levels may still be useful in monitoring programmes limited by time and budget constraints. The major novelty of this study lies in the development of an integrative assessment method based on the following selected ecological indicators: Marinas Environmental Pollution Index (MEPI), Biocontamination Index (BCI), macrofaunal biotic indices (AMBI, M-AMBI, BENTIX, MEDOCC and BENFES), macrofaunal taxa richness and Shannon-Wiener's diversity, and nematode:copepod index. This approach was able to discriminate marinas of the Southern Iberian Peninsula based on their ecological status, which ranged from poor to good. The method can be useful to design standards for assigning "sustainable quality seals" to those marinas with better values of ecological indicators.