Low-velocity shock wave-induced contraction and expansion of nanobubbles can be applied to biocarriers and microfluidic systems. Although experiments have been conducted to study the application effects, the dynamic behavior characteristics of nanobubbles remain unexplored. In this work, we utilize molecular dynamics (MD) simulations to investigate the dynamic behavior characteristics of nanobubbles influenced by low-velocity shock waves in a liquid argon system. The DBSCAN (Density-Based Spatial Clustering of Applications with Noise) machine learning method is used to calculate the equivalent radius of nanobubbles. Two statistical methods are then utilized to predict the time series changes in the equivalent radius of nanobubbles without rebound shock waves. The piston velocity is analyzed using the bisection method to obtain the critical impact states of the nanobubble. The results show that at the low velocity shock wave (piston velocity of 0.1 km s-1), the shock wave pressure is small, the non-vacuum nanobubbles contract and expand in a circular shape, and the gas particles inside the bubble are not dispersed. In contrast, the vacuum nanobubbles collapse directly. As the shock wave rebounds upon impact, it triggers periodic contraction and expansion of the nanobubbles. The predictions indicate that the equivalent radius will vary within a small range according to the pre-predicted values in the absence of the rebound shock wave. Nanobubbles are present in four critical impact states: dispersed gaps, multiple smaller bubbles, two split bubbles, and a concave bubble.