Population modeling has emerged as a critical tool in pharmaceutical research, offering a quantitative framework for understanding drug kinetics, dynamics, and variability across diverse populations. This chapter provides a comprehensive overview of population modeling techniques, including Physiologically-Based Pharmacokinetic (PBPK) models, Bayesian approaches, and nonlinear mixed-effects models, highlighting their pivotal role in drug discovery, clinical trials, and regulatory decision-making. It emphasizes the importance of integrating patient heterogeneity, clinical trial data, and real-world evidence to optimize dosing regimens, assess risk-benefit profiles, and design targeted therapies. The chapter also discusses innovative modeling applications, such as the development of personalized medicine and adaptive trial designs, and addresses challenges in data collection, model validation, and extrapolation. Finally, future trends in pharmacometrics, including advancements in computational methods and systems pharmacology, are explored, underscoring the potential of population modeling to revolutionize drug development and healthcare outcomes.