The molecular detection of transmission of rapidly mutating pathogens such as hepatitis C virus (HCV) is commonly achieved by assessing the genetic relatedness of strains among infected patients. We describe the development of a novel mass spectrometry (MS)-based approach to identify HCV transmission. MS was used to detect products of base-specific cleavage of RNA molecules obtained from HCV polymerase chain reaction fragments. The MS-peak profiles were found to reflect variation in the HCV genomic sequence and the intrahost composition of the HCV population. Serum specimens originating from 60 case patients from 14 epidemiologically confirmed outbreaks and 25 unrelated controls were tested. Neighbor-joining trees constructed using MS-peak profile-based Hamming distances showed 100% accuracy, and linkage networks constructed using a threshold established from the Hamming distances between epidemiologically unrelated cases showed 100% sensitivity and 99.93% specificity in transmission detection. This MS-based approach is rapid, robust, reproducible, cost-effective, and applicable to investigating transmissions of other pathogens.