Effective teaching requires addressing the diverse learning needs of all students through flexible and inclusive approaches. Universal Design for Learning (UDL), originally conceptualized by architect Ronald Mace, offers a framework to create accessible and engaging educational environments. Though UDL is relatively new in education, it has been successfully applied to various products and settings, including textbooks, digital resources, classrooms, and online courses, to accommodate learners from diverse backgrounds. This study explores the application of UDL principles in the context of statistics learning. UDL promotes multiple means of accessing information, expressing knowledge, and engaging learners to enhance motivation and understanding. The three core principles of UDL include: (1) the recognition network, which addresses the "what" of learning by helping students perceive and comprehend information; (2) the strategic network, which focuses on the "how" of learning by supporting students’ planning and execution of tasks; and (3) the affective network, which targets the "why" of learning by fostering engagement and positive attitudes. By integrating these principles, educators can design statistics learning modules that are adaptable to individual student needs, thus improving motivation and educational outcomes. This study underscores the potential of UDL as an innovative approach to make statistics education more inclusive, effective, and motivating for diverse learners.