This paper presents a novel approach by conducting a complexity-based study of an electromechanical (EM) gearbox system with tooth root cracks, utilizing an analytical model and motor current signals for the first time, in contrast to existing studies that primarily use experimental vibration data for complexity-based analyses. The coupled EM model is developed using the modified Lagrangian approach and by incorporating improved time-varying mesh stiffness and gear crack models. Refined composite multiscale dispersion entropy (RCMDE) is employed to evaluate system complexity at various crack depths. The analysis focuses on residual current signals and uncovers an inverse correlation between RCMDE values and the severity of cracks. To demonstrate the efficacy of the proposed approach, a comparison study is conducted between RCMDE and multiscale dispersion entropy (MDE) on both residual current and vibration signals. The results show that RCMDE provides superior stability and effectiveness compared to MDE. Additionally, it has been found that residual current signals offer more robust insights into system complexity than residual vibration signals. This study contributes valuable insights into the behavior of gearbox systems experiencing crack-induced faults, especially concerning short-time series data, highlighting the advantages of using motor current signals and RCMDE for complexity-based analyses.