Workplace fatigue is a pervasive issue causing accidents, additional costs, and decreased productivity. This paper presents a novel methodology for fatigue identification, aiming to enhance worker well-being and business outcomes. The methodology employs wristband captured physiological signals, such as heart rate, and electrodermal activity, to obtain characteristics that serve as objective measures of fatigue. These, when combined with self-reported and observed measures and performance metrics, are used to uncover the fatigue phenomenon using supervised classification methods. The validation of this methodology involved analyzing data from laboratory experiments, where a task mimicking office work was recreated. The Biomonitor wristband was utilized to capture physiological signals in a non-invasive way. The best classification results from the work task experiments was a F1-score of 97.66% using Random Forest. Therefore, the data captured from the Biomonitor wristband and the application of the methodology to identify fatigue were validated. The paper concludes by recommending their use for further research and implementation in industries interested in fatigue management.