Geneticists struggle to identify susceptibility genes for complex diseases. Multifactor Dimensionality Reduction is a crucial machine learning method for gene-gene interaction studies. However, Multifactor Dimensionality Reduction’s exhaustive search for optimal gene combinations can be computationally demanding with large datasets. To overcome this, we propose an enhanced approach using the Gray Wolf Optimizer to reduce computation time in Multifactor Dimensionality Reduction. This method improves the detection of gene-gene interactions efficiently.