The study is entitled Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University. It aims to develop a predictive model of the National Achievement Test performance of Senior High School students. The study intends to extract predictive features of students' National Achievement Test performance, find the extent of the relationship between the students' academic performance in the previous and current year to their National Achievement Test performance, and recommend pedagogical interventions concerning National Achievement Test performance's predictive features. There were two types of datasets, National Achievement Test and Periodic grades of batch 2017 – 2018 when they were in Grade 11 and Grade 12 before taking the National Achievement Test. After the data is collected, the Feature selection and Logistic regression model is applied using the data mining process's rapid miner application. Out of 30 attributes, there are only 14 subjects selected by the feature selection technique. The feature selection selected those subjects which contributed to the prediction. We found out that Philosophy and Arts in the Last Quarter and Semester before the National Achievement Test exam has the most significant effect on the National Achievement Test Result. This study was based on a CMU-funded research entitled Leveraging Educational Data Mining and Machine Learning Techniques in Developing Strategic Interventions for Senior High School Students.