Digital technology and online activities have become a crucial part of student’s life over the past few years. Increased use of portable electronic devices for long hours leads to faulty postures and increased levels of stress resulting in increased prevalence of neck pain and disability. In recent times machine learning innovations provide smart options for assessment and tailored interventions in varied health conditions. The purpose of the study was to explore the effectiveness of Machine learning in assessment and management of neck pain and disability among college students. 30 college students (Mean Age = 21.9 ± 1.40 years) after taking informed consent were selected and assessed for head and neck posture [Cranio-Vertebral Angle, Cranio-Horizontal Angle and Shoulder Sagittal Posture using Artificial Intelligence Posture Evaluation and Correlation System App (Saneftec)], along with neck pain (Copenhagen Neck Function Disability Scale) and disability (Neck Disability Index). Personalized exercises prescribed by app were performed by each subject for 2 weeks followed by reassessment. Results were analyzed using paired t-test that showed significant decrease in neck pain and disability. Slight changes in neck angles (Cranio-Horizontal Angle, Cranio-Vertebral Angle and Shoulder Sagittal Posture) were also observed among college students. (Level of significance—p < 0.05).