Abstract: Preexisting ecological information and plant species occurrence data were used to determine the accuracy and validity of the present regional and subregional wetland indicator status ratings for eight species: Andromeda polifolia, Arctous rubra, Carex canescens, Rhododendron tomentosum, Rubus arcticus, Salix arctica, Salix pulchra, and Viola palustris. Technical documentation was developed to either (1) support the current National Wetland Plant List (NWPL) subregion boundaries and wetland indicator status ratings for the NWPL Alaska Region or (2) support a proposed change to the subregions or wetland indicator status ratings for the NWPL Alaska Region, for inclusion into the next NWPL update. The project developed repeatable, quantitative methods for assignment of wetland indicator status rating. Analyses included multiple correspondence analysis (MCA), analysis of similarities (ANOSIM), nonmetric multidimensional scaling (NMDS), and principal component analysis (PCA). Prevalence index (PI) was used as a numeric approximation of wetland status for comparing observations across subregions. A pilot study on S. pulchra data evaluated regional assignments by machine learning and assessed the feasibility of correlation network analysis and Louvain clustering for wetland indicator status rating assignment as dictated by co-occurring species. The methods developed for this Alaska-specific study may be applied to any future regional or subregional updates to the NWPL.