Lumbar force prediction has been critical to developing cost-effective wearable lumbar exoskeletons to reduce/prevent low back pain (LBP). Noninvasive prediction of the internal compressive forces on the lumbar spine remains challenging. Considering a spine-equivalent beam (SEB) model for the musculoskeletal system, this article presents a two-stage method to identify a set of subject-specific parameters when the upper torso flexes in the sagittal plane. The first stage uses the measured subject-specific spine curvatures due to bending loads to identify the SEB’s flexural rigidity (EI) and erector spinal (ES) muscle force/torque. The second stage searches for the optimal EI minimizing a residual vector based on the difference between the spine shape simulated by the SEB model and that reconstructed from measurements. The results are validated with published in vivo data, considering both with and without lifting a load. The findings reveal that the musculoskeletal structure of a human spine, unlike an engineering beam where EI can be characterized by a well-defined constant for a given material/design, responds to the load acting on it and its parameters depend on the load and its lifting configurations.