The orientation relationships (ORs) between precipitates and a matrix are closely related to the precipitate morphology. A deep understanding of morphological crystallography forms the basis for controlling precipitate shapes and provides scientific guidance for improving the strength and plasticity of materials. The coexistence of multiple ORs has been observed in several precipitation systems, providing opportunities to manipulate precipitate morphology. The Mg–Sn-based alloy is a typical example of such a system. Previous studies have reported 13 ORs between Mg₂Sn and the matrix in this system. These studies explained and predicted these ORs using the preferential matching principle for primary planes. However, this traditional approach alone cannot fully explain why the number of observed ORs is considerably lower than the predicted number. This study systematically analyzes the previous experimental data to further explore the natural preference rules governing the primary planes. By applying lattice matching criteria that considers smaller mismatches and shorter matching vectors, several well-matched vector pairs are identified. However, no vector pair simultaneously exhibits the shortest length and minimal misfit. It is proposed that the presence of multiple well-matched vector pairs contributes to the coexistence of multiple ORs. A systematic analysis of the previous experimental results also reveals that preventing dislocations with long Burgers vectors is an important factor that further constrains the primary facets. A new analytical method focusing on the primary matching column—shared by primary and secondary facets—is introduced. The primary matching column must be parallel to the short Burgers vector of dislocations, unless it is aligned parallel to an invariant or near-invariant line. Based on the characteristics of the primary matching column, the observed ORs are classified, improving our understanding of ORs and explaining why most precipitates lie on the (0001)_α plane. These new findings provide insights into the coexistence of multiple ORs in other systems and contribute to a knowledge base for optimizing precipitate morphologies.