The recent developments in Neurso-Symbolic AI (NESyAI) for healthcare predictive models and explainable techniques have demonstrated immense potential in transforming medical diagnostics and treatment. This chapter dives into the integration of neural networks with symbolic reasoning to enhance both the precision and interpretability of AI systems in healthcare. By harmonising the strength of these approaches, NeSY AI can analyse complex medical data, make accurate diagnoses, and develop effective treatment plans personalised to patients. Applications such as drug repurposing, lung cancer tumour recurrence prediction, and the classification of chronic kidney disease caused from clinical notes exemplify the practical benefits of this hybrid AI approach. Detailed case studies and the methodologies illustrate how NeSY can create more accurate, interpretable and trustworthy examination systems. This dual potential not only boosts patient outcomes but also encourages clinician acceptance, accelerating the integration of AI into mainstream medical fields. Because of these advancements, NeSY holds the promise of significantly enhancing healthcare delivery and patient care.