Online radicalization is a growing societal concern. Extremist groups actively exploit online media to reach wide audiences, spreading ideologies that incite hate and violence. The lack of transparency and conscious use of social media worsens this issue, as users often remain unaware of being targeted by disinformation or radical propaganda. This work analyzes the risk of online radicalization and provides insights for individuals, platforms, and policymakers to mitigate its harmful effects. We conduct a data-driven study to analyze Reddit users’ radicalization risk. We build a temporal classification model using interpretable machine learning to predict the risk of radicalization with features based on recro, a recent social theory of Internet-mediated radicalization. Our findings reveal recro features are strong indicators, with features from later stages having greater influence. We also analyze risk distributions across communities, showing higher risk in controversial groups but also identifying extremists in generic and neutral communities. This result highlights the importance of critical thinking when engaging with online content.