A complex web of factors can influence whether students participate in computer science (CS) during high school. In order to increase participation in CS for all students, there is a need to better understand who is currently participating and what factors might be hindering participation. This study utilized a large-scale, student-level dataset from the Texas Education Research Center to investigate factors that predict high school student participation in CS and advanced CS courses. The dataset contained information on over 1.1 million Texas high school students from the 2017-2018 school year, allowing visibility into CS course availability in schools, student course taking, and detailed demographic information. The researchers used multilevel mixed-effects logistic regression models to explore predictive factors of student participation in CS and advanced CS courses, limiting our analysis to students whose schools offered CS. In both models, the results showed that students who took Algebra I before high school had more than double the odds of being enrolled in a CS course. This work supports and extends previous understanding of factors that are predictive of CS participation in high school, contributing to the existing literature by uncovering the importance of Algebra I before high school as a potential gatekeeper to participation in CS.