Background: The most commonly used classification for proximal fifth metatarsal fractures has not shown good reproducibility. The aim of this study was to evaluate the intraobserver and interobserver agreement of a new classification system for such fractures. Methods: The study involved the development of a novel classification system that categorized these fractures into 2 main types and 2 subtypes. This cross-sectional study included a total of 52 cases that were retrospectively collected to assess the reliability of this system. These cases were then evaluated by 3 independent foot and ankle surgeons who classified the fractures based on the newly established classification system. After 10 months, the same evaluators classified the fractures again. The level of agreement among the evaluators, both internally and externally, was assessed using the kappa coefficient, following the criteria established by Landis and Koch. This framework categorizes agreement levels as slight (0.00-0.20), fair (0.21-0.40), moderate (0.41-0.60), substantial (0.61-0.80), or almost perfect (0.81-1.00). Results: Fifty-two fractures were detected, and 312 evaluations were carried out. The interobserver agreement was substantial when assessing the 2 main types, with a κ value of 0.73, and remained substantial even when considering the subtypes, with a κ value of 0.67. Similarly, the intraobserver agreement demonstrated substantial outcomes when evaluating the 2 main types, with a κ value 0.79. It maintained its significance when including the subtypes, with a κ value 0.77. Conclusion: Lawrence and Botte’s classification identifies 3 primary zones and exhibits moderate interobserver agreement. In contrast, the newly proposed system focuses on only 2 main zones and shows better interobserver agreement. The present study introduces a more precise and reproducible framework that reveals consistency among various observers, including the same observer. This framework may be beneficial for biomedical research as it enhances the ability to compare results across different studies.