Studies shown that school dropout among young people in Brazil corresponds to 3% of the annual GDP and is equivalent to all state and municipal spending on basic education per year. The expectation is that, each year, the country has approximately 575,000 young people without basic education due to school dropout. Many aspects can lead to greater or lesser school dropouts. An important issue that can help to understand this school phenomenon is to disentangle which attributes are inherent to the individual and which are attributed to the setting, so that public policies could be developed in favor of reducing schools' dropouts. In this work, logistic regression methods were applied to the 2019 Nilo Peçanha Platform databases (approximately 250 thousand records). Results shown that demographic, geographic, economic, and school setting variables can be measured to understand their impacts in projecting schools' dropouts, enabling the elaboration and carrying out of preventive and corrective actions in schools. © 2023 IEEE.
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