This research conducts a comprehensive comparative analysis of simulation methodologies for spindle pumps, with a specific focus on steady-state CFD, transient-CFD, and lumped-parameter approaches. Spindle pumps, renowned for their reliability, efficiency, and low noise emission, play a pivotal role in Thermal Management for Battery Electric Vehicles, aligning with the automotive industry’s commitment to reducing pollutants and CO2 emissions. The study is motivated by the critical need to curtail energy consumption during on-the-road operations, particularly as the automotive industry strives for enhanced efficiency. While centrifugal pumps are commonly employed for such applications, their efficiency is highly contingent on rotational speed, leading to energy wastage in real-world scenarios despite high efficiency at the design point. Consequently, the adoption of precisely designed spindle pumps for thermal management systems emerges as a viable solution to meet evolving industry needs. Recognizing the profound impact of simulation tools on the design and optimization phases for pump manufacturers, this research emphasizes the significance of fast and accurate simulation tools. Transient-CFD emerges as a powerful Tool, enabling real-time monitoring of various performance indicators, while steady-CFD, with minimal simplifications, adeptly captures pressure distribution and machine leakages. Lumped-parameter approaches, though requiring effort in simulation setup and simplifying input geometry, offer rapid computational times and comprehensive predictions, including leakages, Torque, cavitation, and pressure ripple. Breaking new ground, this paper presents, for the first time in the literature, accurate simulation models for the same reference machine using the aforementioned methodologies. The results were rigorously validated against experiments spanning a wide range of pump speeds and pressure drops. The discussion encompasses predicted flow, Torque, cavitation, and pressure ripple, offering valuable insights into the strengths and limitations of each methodology.