This study aimed to investigate the relationships between mobility performance assessed using four different classification systems (GMFCS, MACS, CFCS, and BFMF) and the Functional Mobility Scale (FMS) in children with cerebral palsy (CP), as well as the predictive power of these systems on mobility. A total of 100 children with cerebral palsy aged 8–14 years were included in the study. The distribution of GMFCS, MACS, CFCS, and BFMF levels and their relationships with FMS scores at distances of 5 m, 50 m, and 500 m were analyzed. The classification system levels were converted into dummy variables and included in multiple regression models. According to multiple linear regression analyses, GMFCS levels significantly predicted FMS scores at all distances, whereas MACS, CFCS, and BFMF levels did not make significant contributions to the models. Kruskal–Wallis tests based on GMFCS levels revealed significant differences at all distances. In addition, correlation analysis revealed that all classification systems were positively correlated. The strongest correlation was observed between GMFCS and BFMF (r= 0.571, p < 0.001), and the weakest between CFCS and MACS (r= 0.231, p= 0.021). The explanatory power of the regression models for 5 m, 50 m, and 500 m distances was calculated as 56.1%, 57.2%, and 40.6% (Adjusted R²), respectively. These findings demonstrate that GMFCS is the most effective classification system for predicting mobility and may be prioritized in clinical assessments. Moreover, the significant and positive correlations among the classification systems suggest they may be used complementarily in clinical practice.