Human factors research is often focused on the mental workload that is required to perform a task or set of tasks with the goal of reducing workload to make systems easier to manage. The Improved Performance Research Integration Tool (IMPRINT) includes an algorithm to predict mental workload. The algorithm was developed using subject matter expert ratings of workload tasks. We aimed to enhance this capability by developing algorithms using data from four new studies investigating change in performance as demands on mental resources increase. The results indicate three task types of similar difficulty and one task type of much greater difficulty. We then map these to our hypothesized workload function. Finally, we propose a way forward in modeling performance as a function of workload in IMPRINT.