Eastern Black Rails (Laterallus jamaicensis jamaicensis) are notoriously difficult birds to detect because they vocalize infrequently, rarely fly, and inhabit densely vegetated wetlands. As such, there is growing interest in using autonomous recording units (ARUs) to supplement laborious in-person surveys and improve monitoring protocols for this threatened, cryptic species. To provide guidance for biologists considering ARUs to monitor Black Rails, researchers with the NOAA Firebird project conducted several studies to evaluate the utility of ARUs for surveying Black Rails in a variety of contexts. Specifically, we tested detection across a range of distances, vegetation types, and environmental conditions; compared detection rates between in-person observers and ARUs; and evaluated the relationship between Black Rail abundance and calling activity. Additionally, in collaboration with researchers across the range, we evaluated the utility of BirdNET to automate the process of identifying potential Black Rail detections, assessed regional differences and temporal patterns in Black Rail calling activity, and examined the influence of local weather and moonlight on calling activity. Generally, detection rates differed by vegetation cover type and distance, and ARUs were able to detect all three Black Rail call types at least half the time at ~170 m across coastal marsh communities. Calling frequency increased with Black Rail density, and ARUs detected approximately 70% of the calls identified by trained field observers, with a negative relationship between ARU detection rates and wind speed. Hourly calling rates differed regionally, but most detections occurred nocturnally between 2100 and 0400. Lastly, calling activity was influenced by moonlight, cloud cover, and wind speed. Ultimately, our findings demonstrate that ARUs provide a valuable alternative for surveying Black Rails but have limitations worth considering. We will discuss our results in the context of future monitoring needs.