<p>The integration of fractal properties and fractional calculus has emerged as a promising approach in biomedical modeling. This work proposes a fractal–fractional mathematical model to investigate the biological implications of memory and heterogeneity effects in the progression of type 2 diabetes mellitus. The framework incorporates both genetic and non-genetic indicators, thereby capturing heterogeneous pathways influencing the disease dynamics. The present study introduces a mathematical model designed to capture the dynamics of Type 2 diabetes mellitus. Initially, the biological relevance of the fractal–fractional model is ensured through the positivity and boundedness properties. The equilibrium states are also determined, the stability of each steady state is analyzed. Parameter estimation is performed to validate the model using real data from the&#xa0;United Kingdom, reflected with 0.000025789 as sum of squared errors and 0.983 as accuracy coefficient of determination. Sensitivity analysis is conducted to identify the key influencing parameters. Furthermore, the existence and uniqueness of solutions are established using the Banach contraction principle. To obtain numerical approximations, we employ Lagrange polynomials to compute the solutions effectively. Through graphical simulations, we analyze the impact of varying fractal and fractional orders on the system’s behaviour. It is observed that adopting a healthy diet and engaging in regular physical activity can effectively reduce the overall burden of diabetes in the population. The susceptible population declines more rapidly under the influence of non-genetic factors than genetic factors, suggesting a greater impact on the lifestyle-related risk of disease transmission.</p>