Zeolites are a class of crystalline nanoporous materials that are widely used as catalysts, sorbents, and ion-exchangers. Zeolites have revolutionized the petroleum industry and have fueled the 20th-century automobile culture, by enabling numerous highly-efficient transformations and separations in oil refineries. They are also posed to play an important role in many processes of biomass conversion. One of the fundamental principles in the field of zeolites involves the understanding and tuning of the selectivity for different guest molecules that results from the wide variety of pore architectures. The primary goal of my dissertation research is to gain such understanding via computer simulations and eventually to reach the level of predictive modeling. The dissertation starts with a brief introduction of the applications of zeolites and computer modeling techniques useful for the study of zeolitic systems. Chapter 2 then describes an effort to improve simulation efficiency, which is essential for many challenging adsorption systems. Chapter 3 studies a model system to demonstrate the applicability and capability of the method used for the majority of this work, configurational-bias Monte Carlo simulations in the Gibbs ensemble (CBMC-GE). After these methodological developments, Chapter 4 and 5 report a systematic parametrization of a new transferable force field for all-silica zeolites, TraPPE-zeo, and a subsequent, relatively ad-hoc extension to cation-exchanged aluminosilicates. The CBMC-GE method and the TraPPE-zeo force field are then combined to investigate some complex adsorption systems, such as linear and branched C6--C9 alkanes in a hierarchical microporous/mesoporous material (Chapter 6), the multi-component adsorption of aqueous alcohol solutions (Chapter 7) and glucose solutions (Chapter 8). Finally, Chapter 9 describes an endeavor to screen a large number of zeolites with the purpose of finding better materials for two energy-related applications, ethanol/water separation and hydrocarbon iso-dewaxing.