Crowdsourcing allows collecting subjective user ratings promptly and on a large scale. This enables, for example, building subjective models for the perception of technical systems in the field of quality of experience research or researching cultural aspects of the aesthetic appeal. In addition to research in technical domains, crowdsourced subjective ratings also gain more and more relevance in medical research, like the evaluation of aesthetic surgeries. In line with this, we illustrate a novel use-case for crowdsourced subjective ratings of deformational cranial asymmetries of newborns. Deformational cranial asymmetries are deformations of a newborn’s head that might, e.g., result from resting on the same spot for a longer time.Even if there are objective metrics to assess the deformation objectively, there is only a little understanding of how those values match the severity of the deformational cranial asymmetries as subjectively perceived by humans. This paper starts filling this gap by illustrating a crowdsourcing-based solution to collect a large set of subjective ratings on examples of deformational cranial asymmetries from different groups that might have a different perception of those deformations. In particular, we consider pediatricians, parents of children with cranial deformation, and naive crowdworkers. For those groups, we further analyze the consistency of their subjective ratings, the differences of the ratings between the groups, and the effects of the study design.