  Gaokao is the annual academic qualification examination for college
admissions in mainland China. Organized by each provincial-level administrative
region (PAR), Gaokao takes place at the same time nationwide in early June. To
enroll in a university in September, students must take Gaokao and submit
common applications for admission to their home PAR Gaokao office in July,
listing a small and fixed number of universities and majors they intend to
attend and study. About 9.5 million high- school seniors participate in Gaokao
every year, and the Gaokao scores are good for just one year. A student has a
strong chance to be accepted if their Gaokao score is better than the admission
scores of the universities they selected in their applications. However, the
admission scores of universities are unknown at the time when filling out
applications, which to be determined dynamically during the admission process
and may fluctuate from year to year. To increase their chances of acceptance to
a best- suited university, students need to predict admission score of each
university they are interested in. Early prediction methods are empirical
without the backing of in-depth data studies. We fill this void by presenting
well-tested mathematical models based on the ranking of Gaokao scores in a PAR.
We show that our methods significantly outperform the methods commonly used by
teachers and experts, and can predict admission scores with an accuracy of 91%
within a 7-point margin in an exam of a 750-point grading scale.
