The False Negative Rate (FNR) is a metric used to evaluate the performance of a binary classification test, representing the proportion of actual positive cases that are incorrectly identified as negative. Minimizing the FNR is crucial in scenarios where failing to detect a positive case can have severe consequences, such as in medical diagnostics or security screening.