Estuarine biodiversity is impacted by climate change and anthropogenic use due to the high productivity of estuarine ecosystems and convenient human use of nearshore areas. Human use of estuaries (e.g. with dredging, filling, and invasive species introductions) has decimated subtidal and marsh ecosystems, thus making them the focus of major restoration efforts. Submerged aquatic vegetation (SAV) such as eelgrass beds, and their associated communities, fall under these restoration efforts, especially in San Francisco Bay. Diverse eelgrass communities that include grazers, such as Phyllaplysia taylori, have been shown to maintain eelgrass health and promote increased biodiversity. This study addresses the need for simple, predictive models based on field data for use in SAV restoration that incorporates grazer diversity. Predictive models with ecological, abiotic, and landscape variables were generated that explained the presence of P. taylori in eelgrass beds along the coast of the western United States and seasonal patterns in population density. While surprising, the exclusion of abiotic factors in presence/absence model selection suggested that non-point source runoff promotes P. taylori populations via increased food and turbidity, resulting in decreased predation. P. taylori presence within eelgrass beds was best predicted by the positive impacts of nearshore irrigated land, vegetated land, and bare soil land. P. taylori abundance over time within one site was best described by the positive effects of eelgrass density and eelgrass length and the negative effects of epiphytic coverage and average temperature. These models were used to predict habitat suitability for P. taylori in seventeen San Francisco Bay eelgrass restoration areas in various phases of completion, indicating a 53% P. taylori success rate. Incorporating population persistence knowledge from the SAV-associated invertebrate perspective is a step towards grazer community-minded restoration tactics.