Spinal cord injury (SCI) and Parkinson's disease (PD) are debilitating conditions that severely disrupt motor and autonomic functions, profoundly affecting the quality of life for millions worldwide. Over the past few decades, epidural electrical stimulation (EES) has emerged as a promising therapeutic approach to reactivate spinal neural, offering promise as a possible therapy for restoring lost neurological functions. However, the intrinsic inter-individual functional and anatomical variabilities of the spine make the delivery of implantable EES neuroprosthetics challenging. This thesis explores the development of advanced neuroimaging and computational methods to guide the delivery of implantable neuroprosthetics using EES in individuals affected by SCI, PD, and multiple system atrophy (MSA). Recognizing the significant structural and functional variability within the spinal cord, the research emphasizes personalized modeling to enhance the precision and efficacy of medical interventions. The work begins by demonstrating the feasibility of using personalized anatomical models based on high resolution magnetic resonance imaging (MRI) and computed tomography (CT) scans, functional MRI (fMRI), and simulations to guide the implantation of an EES neuroprosthetic. This approach successfully contributed to the restoration trunk and leg motor functions in individuals with complete SCI, highlighting the potential of tailored neuroprosthetic interventions. Building upon this foundation, a novel task-based functional MRI tool for the lumbosacral spinal cord was developed. This tool enables a valuable proof-of-concept for the potential of cord fMRI to map the functional organization of the lumbosacral spinal cord, while also highlighting the challenges involved in this process. Validated across multiple conditions in healthy participants, it addresses the need for functional imaging relevant to spinal cord interventions. Advancements in structural imaging methods further extend personalized modeling to thoracic and cervical spinal regions and across different neurological conditions. By improving and automating structural imaging techniques, the research enhances the accessibility and precision of EES neuroprosthetic guidance for larger patient cohorts. Applications of these methods include addressing orthostatic hypotension in one individual with MSA and 14 SCI individuals, alleviating gait freezing in a single patient with PD and restoring upper limb motor function in an individual with cervical SCI. Enhanced neuroimaging tools also facilitated the implantation of an electrocorticography (ECoG) neuroprosthetic that decode cortical intentions and deliver corresponding spinal stimulation on the same individual with cervical SCI. This brain-spine interface (BSI) restored upper limb motor function in an individual with cervical SCI, solidifying the feasibility of more naturalistic, brain-driven control of neuroprosthetics. Collectively, this work advances the field of neuroengineering by making personalized neuroprosthetic guidance more precise, scalable, and adaptable across neurological conditions. The integration of innovative imaging techniques, automation processes, and brain-controlled strategies paves the way for optimized motor restoration therapies, offering improved quality of life for individuals affected by neurological impairments.