Utilizing hierarchical clustering, we aim to detect technostress by analyzing behavioral constructs such as burnout, Zoom fatigue, information overload, boredom proneness, workload, and neuroticism among Filipino educators. Data from a survey of 303 respondents were subjected to unsupervised learning and analysis. Agglomerative clustering with Ward linkage was employed to form clusters, revealing two distinct groups based on stress levels. Internal validation using the silhouette score confirmed the presence of two clusters. Computing over 5000 bootstrap samples taken, moderate cluster stability was demonstrated based on the Jaccard Index. External validation was conducted using the adjusted Rand score, showing moderate performance also of the clustering algorithm. The high-stress group exhibited significantly elevated scores in the mentioned constructs and was predominantly composed of public sector educators, those with beyond 5 years of teaching experience, and postgraduate degree-holders. These findings highlight the necessity for targeted interventions and professional development programs to manage and mitigate technostress among high-risk demographics, ensuring the well-being and efficacy of educators in a prolonged online learning environment.