Phelan-McDermid syndrome (PMS) is a single-locus cause of developmental delay, autism spectrum disorder, and minimal verbal abilities. There is an urgent need to identify objective outcome measures of expressive language for use in this and other minimally verbal populations. One potential tool is an automated language processor called Language ENvironment Analysis (LENA). LENA was used to obtain over 542 h of audio in 18 children with PMS. LENA performance was adequate in a subset of children with PMS, specifically younger children and those with fewer stereotypic vocalizations. One LENA-derived language measure, Vocalization Ratio, had improved accuracy in this sample and may represent a novel expressive language measure for use in severely affected populations.