Usability experts conduct user studies to identify existing usability problems. An established method is to record gaze behavior with an eye-tracker. These studies require a lot of effort to evaluate the results. Automated recognition of good and bad usability in recorded user data can support usability experts in eye tracking evaluation and reduce the effort. The objective of that bachelor thesis is to identify suitable eye-tracking metrics that correlate with the quality of usability. For this purpose, the central research question is answered: Which eye-tracking metrics correlate with the quality of a web form’s operation? To answer the research question, a quantitative A/B-user-study with eye-tracking was conducted and recorded the gaze behavior of 30 subjects while filling out the web form. The web form was designed, that each web form page was available as a good and bad variant according to known usability guidelines. The results confirm a significant correlation between the eye-tracking-metric "number of visits to an AOI" and the quality of the operation of a web form. The eye-tracking-metrics "number of fixations within an AOI" and "duration of fixations within an AOI" also correlate with the quality of usability. No correlation could be confirmed for the "time of the first fixation within an AOI".