Providing high-pressure compressed gas streams is a desired capability in various applications related to energy storage, transportation, propulsion, and petrochemistry. Oil-free reciprocating piston compressors are commonly employed as boosters across various platforms and over a wide range of flow rates and pressures due to their inherently flexible design [1]. However, modeling such reciprocating compressors become crucial for high delivery pressures since experimentation on new designs is costly. Because of numerous parameters that effect the throughput and operation pressure, the design space is very wide and therefore robust, capable, and reliable modeling approaches are required for rational development of high-pressure boosters. Although a few comprehensive numerical studies on high-pressure reciprocating compressors are available in literature, experimental validation of numerical predictions is rather rare [2-3]. In this study, a multidimensional modeling framework was developed for a high-pressure reciprocating compressor, consisting of both a 0-D mathematical model and a CFD multiphysics model with a deforming mesh by using commercial software. Recognizing that compressor accuracy relies heavily on specific sub-physics, the most important two, (i) check valve dynamics and (ii) heat dissipation were investigated separately [4-5]. To develop a semi-empirical check valve model and to determine the necessary flow coefficients, experimental and CFD investigations were conducted. Similarly, to determine accurate heat transfer coefficients for ambient heat exchange, experimental methods were developed, and they were cross-validated with computational thermal analysis. The integrated compressor models were then compared with experimental data obtained with a commercial booster pump capable of operating pressures up to 750 bar. The comparison indicates that while the CFD model offers detailed resolution of internal pressure and temperature fields, the lumped mathematical model successfully captures the macroscopic behavior. We demonstrate that both models provide critical information regarding discharge pressures and mass flow rates, offering a validated toolset for both rapid prototyping and detailed design.