Cognitive assessment and training through computerized methods are excellent concepts for maintaining cognitive function during occupational/operational challenges. Multitasking is required during various military operations, which creates a mental workload. Optimum working memory (visual, spatial, and auditory) capacity helps to maintain mental workload. The proposed research emphasizes assessing the mental workload using eye-tracking measures during a desktop-based dual N-back task comprising three sub-stages (n = 1, n = 2, n = 3). A wearable eye tracker was used to acquire the eye tracking data from 29 individuals, and the NASA Task Load Index (NASA-TLx) Score was utilized to calculate the assessed mental workload. The study found associations between participant accuracy on the Dual N-Back test and Pupil Diameter, Shannon Entropy, and Fixation Count. These results expand our understanding of the cognitive mechanisms behind dual N-Back tasks and their connection to mental workload. Higher mental workload has been associated with lower fixation count and accuracy, as fixation count and accuracy showed inverse associations with workload. On the other hand, pupil diameter showed a positive association with workload, indicating that higher levels of mental workload were associated with larger pupil dilation. The K-Means Clustering Algorithm, Decision Tree, and Random Forest Classifiers were trained using the generated dataset, and the corresponding accuracies were also derived to use the study results conclusively.