Dance requires effective functional movement for the prevention of injury, with implications for the biomechanical response to performance. This study investigated the efficacy of the Functional Movement Screening (FMS) in predicting mechanical loading during the Dance Aerobic Fitness Test (DAFT). Twenty-five university dancers (19 females; age: 20.3 ± 0.94 years; height: 162.55 ± 0.05 cm; mass: 58.73 ± 6.3 kg; and 6 males; age: 21.08 ± 2.01 years; height: 175 ± 6.54 cm; mass: 68.16 ± 4.97 kg) were screened using the FMS. Subjects then completed the DAFT with a GPS-mounted triaxial accelerometer located at the cervico-thoracic junction. Accelerometry data were sampled at 100 Hz and used to calculate total accumulated PlayerLoad, Playerload medial-lateral (PL ML ), PlayerLoad anterior-posterior (PL AP ), and PlayerLoad vertical (PL V ) over the duration of the DAFT. Linear regression analysis was used to determine the strength of correlation between FMS and PlayerLoad, PL ML , PL AP , and PL V , and forward stepwise hierarchical modelling was performed to establish which FMS components were the primary predictors of mechanical loading. The Deep Squat (DS) demonstrated statistical significance for PL VTotal and PL Total . The non-dominant Hurdle Step (HS) was a statistically significant predictor of PL MLTotal . The FMS composite score was a statistically significant predictor for PL VTotal . Forward stepwise regression analysis demonstrated that DS was the sole predictor for PL Total and the primary predictor for PL VTotal . Non-dominant HS was identified as the primary predictor of PL MLTotal . It is concluded that the DS, non-dominant HS, and the FMS composite score can be used to predict mechanical loading in performance of the DAFT, which may have implications for dance performance and injury prevention.