Post-Traumatic Stress Disorder (PTSD), Obsessive–Compulsive Disorder (OCD), and childhood trauma are significant mental health issues that require effective therapeutic interventions. Neuro-Linguistic Programming (NLP) with Visual/Kinesthetic (V/K) dissociation technique and Swish Patterns are promising approaches for treating these conditions. When combined with Machine Learning (ML), these methods can be significantly enhanced. This chapter explores the integration of NLP and its techniques V/K dissociation and Swish Patterns with ML to create personalized, adaptive, and effective treatment plans. Machine learning's capabilities in data analysis, predictive analytics, real-time monitoring, and virtual reality (VR) integration provide a robust framework for optimizing therapeutic techniques. This integrated approach aims to improve treatment outcomes, foster emotional recovery, and empower individuals to reclaim control over their mental health. In this research, we identified 26 states across the US based on Data tables (from Child Maltreatment 2018), that were eligible based on the topic of Childhood PTSD and Trauma Treatment. From these, we were able to pinpoint the top four states with the highest prevalence of anxiety, OCD, and PTSD among child patients.