This argument-based validation research investigates the validity of score interpretations on a computer-based, graphic-prompt writing test, focusing on the generalization inference. The graphic-prompt writing test assesses examinees’ ability to incorporate visual graphic information into their writing,. Both analytic ratings on Graph Description, Content Development, Organization, and Grammar/Vocabulary (n = 2,424) and composite ratings (n = 606) on written test responses from 101 ESL students were analyzed using Generalizability (G) Theory and Multi-Faceted Rasch Measurement (MFRM). Findings indicated three of the four analytic scales and the composites yielded dependable scores. In addition, the results of the G-studies and MFRM analysis revealed the relative effects of the raters on the total score variance was not trivial for both composite and analytic scores and the three raters were not quite equivalent in their rating severity. Nevertheless, the findings support the generalization inference to a large extent. Thus, it can be claimed the graphic-prompt writing task scores were dependable enough to be used for the intended purposes, particularly with the two-rater and three-task test administration design.