Assembly lines are essential components of manufacturing operations but often face challenges due to variable operation times and ergonomic risks leading to increased musculoskeletal disorders (MSDs) and associated economic burdens such as absenteeism and workers’ compensation. Assembly line balancing approaches frequently overlook these issues and their impact on worker well-being, highlighting the need for models that integrate both ergonomics and variable operation times. This paper introduces a new scenario-based optimization model for assembly line balancing, incorporating a fatigue and recovery ergonomic assessment. The model aims to reduce worker fatigue by considering the variability of operation times across different scenarios and their probabilities. An Integer Linear Program (ILP) is developed and efficiently solved using an Iterative Dichotomic Search algorithm. A simulation framework evaluates the model’s robustness and supports dynamic managerial policies such as job rotation, overrun policies, and scheduled rest allowances. Numerical experiments demonstrate the effectiveness of the proposed approach in improving ergonomic conditions and reducing the risk of MSDs without compromising production efficiency. Implementing the model enables managers to proactively address worker fatigue, enhancing well-being, increasing productivity, and achieving significant cost savings through reduced absenteeism and lower compensation claims. The model also provides actionable insights for managerial decision-making to improve resource allocation and strategic planning. By aligning with Industry 5.0 principles, the approach fosters sustainable, human-centric production systems, offering competitive advantages. The method’s adaptability provides practical solutions that enhance operational management and contribute to long-term organizational success by balancing worker health with economic efficiency.