The Polygenic Risk Score (PRS) research domain holds great promise for significant contributions to precision medicine by providing insights into genetic predispositions for common diseases. However, the field faces challenges in terminology standardization and precise conceptualization, which hinder domain comprehension and consequently the effective data management and application in clinical practice. With the aim of providing clarification in domain-specific terms and relationships, in this paper we apply conceptual modeling techniques to the PRS research domain. We develop two conceptual models, one for the definition of a PRS Model and another for defining the PRS Models in context, in order to clarify terminology and disambiguate concepts typically used in studies. Finally, we instantiate a study as a use case which illustrates how the proposed solution clarifies the domain. Our approach enhances domain comprehension and promotes standardization. In addition, it serves for the benchmarking of PRS Models, helping clinicians to better select PRS Models for practical application in clinical settings.