In today’s rapidly evolving digital era, the ability to think computationally is no longer confined to computer science it has become essential across disciplines, including mathematics. This study integrates computational thinking (CT) into mathematics learning by analyze its development, benefits, and implementation challenges. Computational thinking which includes abstraction, algorithms, decomposition, and pattern recognition, is considered a crucial component in improving students' mathematical learning. These insights are intended to inform educators, policymakers, and researchers seeking to align mathematics instruction with contemporary technological and pedagogical advancements. Utilizing a systemic literature review as a qualitative method, by 37 peer-reviewed articles published between 2019 and 2024 in the Scopus database were examined. Through qualitative thematic analysis, key insights were identified across cognitive and affective dimensions. The review suggests that CT may support students’ development in problem-solving, logical reasoning, and conceptual abstraction, while also contributing to affective aspects such as motivation, self-confidence, and self-regulated learning. However, several barriers hinder its effective implementation, including insufficient teacher training, limited infrastructure, and curricular constraints. The study highlights the necessity for targeted teacher training initiatives and institutional support to facilitate CT integration.