Infrared imaging (IRI) can detect airflow through and near respirator masks based upon temperature differences between ambient and exhaled air. This study investigated the potential usefulness of IRI for detecting leaks and providing insight into the sites and significance of leaks. Subjects (n = 165) used filtering facepiece N95 respirators (N95 FFR) in the course of a research study concerning training modalities. Short sequence video infrared images were obtained during use and with intentionally introduced facial seal leaks. Fit factor (FF) was measured with condensation nuclei count methods. IRI detected leaks were scored on a four-point scale and summarized as the Total Leak Score (TLS) over six coding regions and the presence or absence of a "Big Leak" (BL) in any location. A semi-automated interpretation algorithm was also developed. IRI detected leaks are particularly common in the nasal region, but these are of limited significance. IR imaging could effectively identify many large leaks. The TLS was related to FF. Although IRI scores were related to FF, the relationship is insufficiently close for IRI to substitute for quantitative fit-testing. Using FFRs infrared techniques have potential for identifying situations with very inadequate respiratory protection.