This study introduces a logistic regression-based stress level metric to (1) assess stress levels of Air Traffic Controllers (ATC) and pilots, and (2) detect off-nominal events using audio-derived features. With over 16,264 labeled ATC-pilot utterances and scalar and multi-dimensional speech attributes, it is demonstrated that a developed Stress Score metric can capture meaningful distinctions between the nominal and off-nominal utterances. The Beta distribution fit further captures the skewed nature of Stress Scores, indicating that the model follows a non-linear but quantifiable pattern...