The objective of this study was to assess the plausibility of using computational cognitive models for evaluating the usability of human–machine interfaces in supervisory control of high-throughput (biological) screening (HTS) operations. Usability evaluations of new interface prototypes were conducted by comparisons with existing technologies. Model assessment occurred through comparison with human test results. Task completion times and the number of errors were recorded during human performance trials, and task time was predicted in cognitive model trials in tests with two HTS interfaces. Computational GOMSL (Goals, Operators, Methods, and Selection rules Language) models were constructed based on a combination of cognitive task analyses (abstraction hierarchy modeling and goal-directed task analysis). The usability tests revealed improvements in task performance with the new prototypes. The cognitive model outputs were correlated with actual human performance, and the approach was considered useful for evaluating the usability of new interfaces in life sciences automation in the future.