Cryogenic minimum quantity lubrication (CMQL) has emerged as a promising technique to enhance lubrication performance in the realm of cryogenic machining, addressing several challenges traditionally associated with lubrication in extreme temperature environments. Despite its potential, the lack of a clear understanding of the intricate relationships among various parameters of CMQL, cutting parameters, and resultant machining performance has hindered its broader industrial adoption. This paper aims to elucidate these relationships through a comprehensive analysis of the supply system, machining performance, lubrication mechanisms, and theoretical models pertinent to cryogenic minimum quantity lubrication. Initially, various supply methods employed for CMQL during machining operations are explored. These methods are crucial as they dictate the efficiency and effectiveness of lubricant delivery to the cutting interface. Innovative techniques such as spray systems, mist delivery, and direct application are explored, each presenting unique advantages in ensuring optimal lubricant distribution, which is essential for maximizing the beneficial effects of cryogenic cooling and lubrication. Subsequently, the superior performance of CMQL is evaluated in terms of critical machining parameters including cutting force, tool wear, and chip deformation. Empirical evidence demonstrates that CMQL significantly improves lubrication efficacy, leading to a marked reduction in cutting forces when juxtaposed with traditional dry cutting methods. This reduction is not merely quantitative; It translates into enhanced tool life and improved surface finish quality, which are pivotal for industrial applications where precision and reliability are paramount. Moreover, a detailed analysis of the interaction between CMQL parameters and cutting parameters reveals that the feed rate and the cutting speed are the most influential factors affecting the cutting force. Increases in either parameter result in elevated cutting forces, underscoring the need for meticulous optimization. By adjusting these parameters thoughtfully, manufacturers can mitigate cutting forces, thereby achieving a more efficient machining process. To facilitate this optimization, strategic approaches for refining machining parameters are summarized. These strategies encompass a holistic consideration of the machining environment, tool material properties, and the physical characteristics of the workpiece. The culmination of these efforts leads to the identification of relatively optimal machining parameters, which not only enhance performance but also align with economic considerations in industrial settings. In conclusion, while CMQL presents a revolutionary step forward in machining technology, several bottlenecks remain that necessitate further investigation. Future research directions should focus on developing a more nuanced understanding of the interactions between CMQL parameters and machining dynamics. This includes exploring advanced modeling techniques that can accurately predict performance outcomes based on varying operational conditions. Additionally, the integration of real-time monitoring systems could provide invaluable feedback, allowing for adaptive control of the lubrication process. By addressing these challenges, the full potential of cryogenic minimum quantity lubrication can be unlocked, paving the way for its wider application across diverse manufacturing sectors. This research not only contributes to the academic discourse but also serves as a practical guide for industrial practitioners seeking to enhance machining performance through innovative lubrication techniques.