The nature of mathematics is inherently abstract, built on symbols, axioms, and logical frameworks rather than physical entities. Despite this abstraction, mathematics has profound and far-reaching applications in the real world. Its scope is vast, ranging from pure areas such as number theory, which explores the properties and relationships of numbers, to applied fields like calculus, statistics, and complex systems modeling. These mathematical tools allow us to simulate and analyze everything from the spread of diseases to financial markets and ecological systems. In the Theory of Knowledge (TOK) context, this duality—of abstraction and application—raises important questions about the role and reliability of mathematical knowledge. TOK encourages us to reflect on how mathematics helps us make sense of the world and interpret phenomena across a range of disciplines, such as physics, economics, and even social sciences. However, it also prompts us to examine the boundaries of its usefulness. While mathematical models can simplify reality and provide predictive power, they often rely on assumptions that may not hold true in unpredictable or complex real-world conditions. For example, modeling human behavior or natural disasters involves uncertainty that cannot always be accurately captured through equations. This limitation reminds us that, although mathematics aspires to objectivity and precision, it operates within a framework constructed by humans—and thus may be constrained by simplifications, idealizations, and interpretative choices. Through such reflections, TOK challenges us to consider not only the power of mathematics but also its epistemological limits, especially in areas where uncertainty, variability, or subjectivity are central.