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In this review, we analyze the current state of the art of compu- tational models for in-vehicle User Interface (UI) design. Driver distraction, often caused by drivers performing Non Driving Re- lated Tasks (NDRTs), is a major contributor to vehicle crashes. Accordingly, in-vehicle UIs must be evaluated for their distraction potential. Computational models are a promising solution to au- tomate this evaluation, but are not yet widely used, limiting their real-world impact. We systematically review the existing literature on computational models for NDRTs to analyze why current ap- proaches have not yet found their way into practice. We found that while many models are intended for UI evaluation, they focus on small and isolated phenomena that are disconnected from the needs of automotive UI designers. In addition, very few approaches make predictions detailed enough to inform current design pro- cesses. Our analysis of the state of the art, the identified research gaps, and the formulated research potentials can guide researchers and practitioners toward computational models that improve the automotive UI design process.