To examine increasing concerns regarding digital dependence, this study uses machine learning techniques to measure students’ dependency on electronic devices. As academic and social activities gradually depend more on smartphones, computers, and tablets, the potential risks posed on one’s mental health and academic performance become much greater. The study analyzes multiple machine learning algorithms to calculate the trends for factors like screen time, usage behaviors, and other psychological variables that contribute to dependence on devices. Using surveys, along with usage analytics, makes it possible to construct a model that will predict the likelihood of addiction toward the analyzed devices. This obsession with technology serves as vital indicators for preventing its overindulgence, preparing educators and parents for the initiation of healthy digital habits. It also shall be beginning the tide toward more comprehensive talks, thus adding to the understanding of the phenomena of technological dependence on how best to achieve the balance and safety enhancements of digitization in education. These are steps that you can implement to minimize the risks of developing such dependency, while still using technology within an ecosystem of learning and communication.