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The effect of stress on the human body is substantial, potentially resulting in serious health implications. Furthermore, with modern stressors seemingly on the increase, there is an abundance of contributing factors which lead to a diagnosis of acute stress. However, observing biological stress reactions usually includes costly and time consuming sequential fluid-based samples to determine the degree of biological stress. On the contrary, a speech monitoring approach would allow for a non-invasive indication of stress. To evaluate the efficacy of the speech signal as a marker of stress, we explored, for the first time, the relationship between sequential cortisol samples and speech-based features. Utilising a novel corpus of 43 individuals undergoing a standardised Trier Social Stress Test (TSST), we extract a variety of feature sets and observe a correlation between speech and sequential cortisol measurements. For prediction of mean cortisol levels from speech, results show that for the entire TSST oral presentation, handcrafted COMPARE features achieve best results of 0.244 root mean square error [0 ;1] for the sample 20 minutes after the TSST. Correlation also increases at minute 20, with a Spearman’s correlation coefficient of 0.421, and Cohen’s d of 0.883 between the baseline and minute 20 cortisol predictions.