Introduction: Suicide is one of the leading causes of death among individuals aged 10 to 30 years. As most studies in young adults have been done in university or college students, the generalizability of the current evidence to the group of students in vocational education is limited. It is therefore pivotal to create an evidence base for suicide prevention within the school setting that is inclusive of different educational levels. Aim: To identify the prevalence and high risk groups of suicidal thoughts (ST) and suicide attempts (SA) over the past 10 years. Methods: Repeated cross-sectional design. The data was collected from Dutch students in vocational education aged 15-23 years old, who completed a web-based questionnaire “Test your Lifestyle” (N=101.182) in the period 2013-2023. Logistic regression analyses were performed for descriptive analyses and a machine learning model developed by Berkelmans et al. (2023) was used for the high risk identification. Results: The first results showed that among vocational school students, both ST and SA were significantly predicted by female gender (ORST=1.44, ORSA=1.11), middle age (i.e. 18-20 years, ORST=1.19, ORSA=1.22) or older age (i.e. 21-23 years, ORSA=1.42), recent schoolyears (i.e. 2019-2023, ORST= 1.28, ORSA=1.11) and largely by a high risk for anxiety and mood disorders (ORST=51.8, ORSA=14.7). The results of the machine learning analyses will also be presented to share insights about interaction effects that may increase or reduce the risk for suicidal thoughts and behaviour. Conclusion: Our study will provide scientific evidence to support depression and suicide prevention programmes among vocational school students. This is not only important for the well-being of these students but it may also contribute to a healthy working population.