Scientific modelling is a fundamental methodological tool used across various scientific disciplines to abstractly represent and study real-world systems that are too complex, too large, or too dangerous to be observed directly. These models range in form from simplified mathematical equations and computational simulations to scaled physical representations, each designed to isolate variables and predict system behavior under specific conditions. By reducing complex reality into manageable parameters, modelling allows researchers to test hypotheses, visualize potential interactions, and forecast outcomes—such as climate change patterns, epidemic spread, or material failure—thereby guiding experimental design and informing theoretical understanding without requiring the immediate practical existence of the phenomenon being studied.