Critical thinking is a fundamental skill, making it a cornerstone of effective education. The relationship between teachers’ beliefs about creativity and critical thinking and their classroom implementation is always crucial. The primary objective of this study is to conduct an in-depth analysis of how teacher beliefs influence classroom practices using machine learning predictive models by identifying specific patterns and correlations that illuminate the impact of these beliefs on teaching practices. Furthermore, it explores the possibility of classifying teachers into distinct profiles based on the alignment and variation in their beliefs and practices. For Research Question 1, Random Forest Regression outperformed Linear Regression (R2 = 0.80, MSE = 0.11 compared to R2 = −0.43), capturing 80% of the variance in classroom practices and emphasizing the consistency of teacher beliefs as a key predictive factor. For Research Question 2, KMeans clustering identified three distinct teacher profiles: (1) high beliefs but low practices, (2) low beliefs and low practices, and (3) moderate beliefs with high practices. The classification was validated by a Silhouette Score of 0.53. These findings offer valuable insights for teacher training and policy development, underscoring the need for tailored interventions that better align teacher beliefs with their classroom practices, thereby promoting critical thinking and creativity in educational settings.