Background: The scale of environmental damage caused by plastic pollution highlights the need to implement sustainably sourced biodegradable plastics within the global economy. Microalgae biofilms cultivated on rotating algae biofilm reactors (RABRs) using anaerobically digested municipal wastewater provide a feedstock for bio-based and biodegradable bioplastic production for practical environmental management applications. Algix, LLC, a company based in Meridian, Mississippi, specializes in manufacturing bioplastic products from microalgae suspended in aqueous environments [1]. Algix, LLC manufactures bioplastics for multiple products, including shoes and agricultural mulch films. The Sustainable Waste-to-Bioproducts Engineering Center at Utah State University (USU) in Logan, Utah collaborated with Algix, LLC and the 230,000 m3/day Central Valley Water Reclamation Facility in Salt Lake City, Utah to create a bio-based polyester using microalgae biomass cultivated on an 11.4 m3 pilot-scale rotating algae biofilm reactor (RABR). While the physicochemical properties of the bioplastics have been described [2], the biodegradation characteristics of this bio-based polyester have not been evaluated. The purpose of this research was to investigate the biodegradation of biofilm microalgae-based bioplastic under temperature- and moisture-controlled conditions in a full-scale composting system at CVWRF.  Methods: ASTM Method D6400 was used to quantify the biodegradability of thin-film samples of the bioplastic composed of 30% algae biomass over a 16-week period.  Results: Thin film samples of the algae-based bioplastics were reduced in mass from 5 g to less than 0.01 g and in size from 8500 mm2 to particle sizes less than 40 mm2 after 16 weeks. A polyethylene negative control showed no disintegration based on mass loss and size reduction. Conclusions: Bioplastic samples made from RABR-cultivated algae biofilms retained no measurable mass on a 6.35 mm sieve after 16 weeks of aerobic composting. However, further studies utilizing triplicate conditions for each plastic sample are recommended to increase the statistical robustness of the resulting data.