<italic>Contributions:</italic> Prior studies on education have mostly followed the model of the cross-sectional study, namely, examining the pretest and the posttest scores. This article shows that students’ knowledge throughout the intervention can be estimated by time-series analysis using a hidden Markov model (HMM). <italic>Background:</italic> Analyzing time series and the interaction between the students and the game data can result in valuable information that cannot be gained by only cross-sectional studies of the exams. <italic>Research Questions:</italic> Can an HMM be used to analyze the educational games? Can an HMM be used to make a prediction of the students’ performance? <italic>Methodology:</italic> The study was conducted on (<inline-formula> <tex-math notation="LaTeX">$N=854$ </tex-math></inline-formula>) students who played the Save Patch game. Students were divided into class 1 and class 2. Class 1 students are those who scored lower in the posttest than class 2 students. The analysis is done by choosing various features of the game as the observations. <italic>Findings:</italic> The state trajectories can predict the students’ performance accurately for both classes 1 and 2.