Amidst the pervasive impact of the COVID-19 pandemic, student mental health stands as a paramount public health concern. This vulnerability is exacerbated by the hectic lifestyles of students, rendering them particularly susceptible to the implications of social distancing measures. The primary objective of this research is to assess the self-reported levels of stress, anxiety, and depression among Serbian students. This evaluation encompasses a comprehensive examination of demographic traits, living and learning environments, students' activities during the epidemic, potential exposure to the coronavirus, and overall mental and physical health. The core aim of this article is to prognosticate the mental health of students under the unprecedented circumstances posed by the pandemic. Leveraging the power of PandemicPulse, this SVM-enhanced forecasting model, this research meticulously analyzes a dataset obtained from a dedicated student mental health survey website. The application of appropriate classifiers allows us to draw meaningful insights and predictions regarding mental health outcomes. In this discourse, this study unveils a multifaceted approach, employing multiple classifier strategies to ensure the highest accuracy in forecasting student mental health. This research endeavors to harmonize understanding, utilizing PandemicPulse as a guiding rhythm to navigate the complex landscape of student well-being during these challenging times.