Companies in a variety of industries rely on their employees to work together effectively in teams to achieve their objectives. However, finding ways to encourage collaborative behavior to optimize a team’s performance is often challenging. In particular, managers would like to be able to increase the likelihood that team members decide to help each other, in the event of workload imbalances (e.g., due to worker absences). Such behavior could be encouraged by leveraging the inherent characteristics of individual team members (e.g., their personality traits) such that the decision to help is driven by internal motivations, rather than external rewards. This research seeks to explore the potential for increasing team helping behavior through the development of an agent-based simulation model of a team of assembly line workers. Model inputs were derived from previous experiments with human participants, in which data on participants’ personalities, perceptions, and decisions to help team members complete a task were captured. The model enables a variety of “what-if” scenarios to be performed to test the impacts of personality and perceptions on helping behavior, with a goal of providing a practical tool that will help managers better understand how to maximize workforce performance.