Influenza virus continues to pose a significant global health threat, causing seasonal epidemics and occasional pandemics. Mathematical modeling is vital to understand the dynamics of influenza virus transmission and shaping effective control strategies. This chapter provides an overview of mathematical insights into influenza virus dynamics, including compartmental models, evolutionary models, and agent-based models. These mathematical approaches allow researchers to simulate the spread of influenza within populations, assess the impact of interventions, and predict the emergence of novel strains. Challenges in model validation, data integration, and interdisciplinary collaboration are discussed, along with future directions for advancing the field. By integrating mathematical modeling with epidemiological data and molecular biology techniques, researchers can gain a deeper understanding of influenza virus transmission dynamics and develop more effective strategies for prevention, control, and pandemic preparedness. This chapter underscores the importance of mathematical insights in unraveling the complexities of influenza virus dynamics and guiding evidence-based public health interventions.