This study presents a compact thermal management model for Li-ion battery packs, with a specific focus on Tesla Model S vehicles. The model, which utilizes a detailed thermal resistance network, provides faster results than traditional Computational Fluid Dynamics (CFD) tools, making it approximately 10.5 times faster without compromising on comprehensive assessment. Key factors such as the C-rate and initial fluid temperature were found to significantly impact battery temperature and the maximum temperature difference. For instance, as the C-rate increases from 0.5 to 5, the average battery temperature rises by 84.5 degrees C, a condition that would lead to thermal runaway in practical scenarios. Meanwhile, an increase in the initial fluid temperature from 15 degrees C to 30 degrees C results in an approximate increase of 13.2 degrees C in the average battery temperature. The coolant velocity also plays a crucial role in managing heat dissipation from the batteries. The model, offering easy customization and reduced computational complexity, is ideal for modeling and simulations of Li-ion battery modules and packs. This research significantly contributes to improving the efficiency and safety of Li-ion batteries, particularly in electric vehicles, providing valuable insights for the design and analysis of battery thermal management systems (BTMS).