Exercise is central to neurological rehabilitation, yet standardized, one-size-fits-all prescriptions frequently fail to reflect the heterogeneity of impairment, disease trajectory, and personal context that characterize conditions such as stroke, Parkinson's disease (PD), multiple sclerosis (MS), spinal cord injury (SCI), and traumatic brain injury (TBI). This narrative review summarizes current evidence on individualized exercise prescription in neuro physiotherapy and identifies the factors that shape exercise selection, progression, and monitoring. A structured search of PubMed, Google Scholar, and Scopus-indexed literature was conducted, yielding evidence from randomized controlled trials, feasibility studies, systematic reviews, and clinical practice guidelines. Across conditions, individualization is most often anchored to physiological baselines - cardiopulmonary exercise testing, heart-rate reserve, one-repetition maximum, and rating of perceived exertion - with re-assessment at fixed intervals to adjust load. Disease-specific staging systems (Hoehn and Yahr stage, Expanded Disability Status Scale, American Spinal Injury Association Impairment Scale) and patient-level modifiers, including fatigue, cognition, comorbidity burden, self-efficacy, and motivation, further shape prescriptions. Wearable sensors, telerehabilitation platforms, and artificial-intelligence-driven decision-support tools increasingly enable continuous, adaptive personalization, though most such tools remain in feasibility or protocol stages and artificial-intelligence-generated programs still show limited precision and safety-biased conservatism compared with expert clinical judgment. Dose parameters - frequency, intensity, time, and progression - remain inconsistently reported across the literature, constraining reproducibility and evidence synthesis. This review recommends standardized dose reporting (aligned with the FITT-VP framework), wider adoption of physiological-threshold-anchored prescription, and cautious, clinician-supervised integration of digital and AI-based tools to advance truly individualized neuro-physiotherapy practice.