This review explores the impact of mobile phone addiction on studies, health, and home life based on machine learning methods. In contrast to previous research focusing on one aspect, e.g., sleep quality or study stress, the present investigation employs machine learning to detect patterns of phone dependence and its extended effects. Excessive use of mobile phones has been shown to negatively impact academic performance by instigating poor time management, distraction, and sleep deprivation, which translates to decreased grades. It decreases the quality of sleep, causing lethargy and cognitive problems. Additionally, excessive use of mobile phones damages family and social relationships since individuals tend to give preference to online relationships over actual ones. With the application of machine learning models, it is feasible to forecast individuals at risk and negative outcomes, thereby informing targeted interventions. Also, this review compares different methodological strategies, such as ML-based investigations into the detection of depression, overuse of mobile phones, online game addiction, and their effects of health and relationships.