The emergence of Batrachochytrium salamandrivorans (Bsal) poses an imminent threat to caudate biodiversity worldwide, particularly through anthropogenic-mediated means such as the pet trade. Bsal is a fungal panzootic that has yet to reach the Americas, Africa, and Australia, presenting a significant biosecurity risk to naïve amphibian populations lacking the innate immune defenses necessary for combating invasive pathogens. We explored the capability of near-infrared spectroscopy (NIRS) coupled with predictive modeling as a rapid, non-invasive Bsal screening tool in live caudates. Using eastern newts (Notopthalmus viridescens) as a model species, NIR spectra were collected in tandem with dermal swabs used for confirmatory qPCR analysis. We identified that spectral profiles differed significantly by physical location (chin, cloaca, tail, and foot) as well as by Bsal pathogen status (control vs. exposed individuals; p < 0.05). The support vector machine algorithm achieved a mean classification accuracy of 80% and a sensitivity of 92% for discriminating Bsal-control (-) from Bsal-exposed (+) individuals. This approach offers a promising method for identifying Bsal-compromised populations, potentially aiding in early detection and mitigation efforts alongside existing techniques. Near-infrared spectroscopy validated by polymerase chain reaction enables rapid detection of chytrid fungus in eastern newts, offering a practical surveillance strategy to mitigate harmful pathogen spillover.