This study was conducted to explore the effects of different survival methods on the vital signs and quality indices of Crassostrea hongkongensis and to establish a prediction model. Three hundred oysters were divided into a control group (CK), purification group (PL), and ecological ice temperature dormancy group (PD). The experimental period was 9 days without water. The survival rate, microbial content, vital signs (heart rate, contraction rate, adductor muscle tension, mantle response time index) and nutritional quality (crude protein, glycogen, water, lactic acid, etc.) of each group were monitored every day. The results showed that the survival rate of the PD group was 96% after 9 days of survival, which was significantly higher than those of the CK group (61%) and PL group (70%). The mass loss rate of oysters in the PD group was 4.78%, which was significantly lower than those of the CK group (15.99%) and PL group (11.68%). The results showed that purification and ecological ice temperature dormancy treatment of C. hongkongensis significantly reduced mass loss during water-free survival, and ecological ice temperature dormancy and water-free survival treatment after temporary culture purification slowed microorganism growth. Among the vital signs evaluated, the decrease in heart rate (79.55%) and loss of adductor muscle tension were lower in the PD group than in the other groups, indicating alleviation of stress injury, an increase in the edge contraction rate, and slower mantle response time in the PD group. Among nutritional quality indicators, glycogen and fat consumption were significant. With the extension of the survival time of glycogen, the glycogen content in the CK group increased significantly more than that in the other two groups, and the change in the lactic acid content in each group increased with prolonged survival times. However, overall, the range of changes of quality indicators in the PD group was smaller than those in the other two groups. Additionally, quality reduction was lower in the PD groups than in the other groups, indicating that ecological ice temperature dormancy in the PD group slowed quality reductions by reducing the metabolic rate. Among the indicators of oxidative stress, the catalase activity in the CK group showed a fluctuating upward trend throughout the survival time and increased significantly at KA5d (survival time) (P＜0.05). The catalase activity of the PL and PD groups showed a gradually increasing trend, indicating that under dual stress, the body's oxidative stress was enhanced. Catalase, an antioxidant enzyme, responded to oxidative stress to clear the accumulated hydrogen peroxide in the body and protect cells from oxidative damage. Correlation analysis of the vital signs and quality indicators in the PD group showed that crude protein, glycogen, heart rate, edge contraction rate, adductor muscle tension, and mantle response time were strongly correlated. Based on the results, a multiple linear regression equation was established. The predictive regression equation was used to determine whether there was a collinearity problem between samples by the variance inflation factor value. Durbin-Watson statistics were used to evaluate the independence of samples, and R² was used to evaluate the fitting degree of the established model. Considering the above factors, a model with crude protein as the dependent variable was established: y = 8.298+0.003x₁–0.051x₂–0.046x₃–0.082x₄, where y is crude protein, x1 is the heart rate, x2 is the edge contraction rate, x₃ is muscle tension, and x₄ is the mantle response time, and R²=55.2%. The model with glycogen as the dependent variable was as follows: y=9.404–0.013x₁+0.829x₂+0.224x₃–1.945x₄, where y is glycogen, x₁ is the heart rate, x₂ is the shrinkage rate, x 3 is muscle tension, and X4 is the mantle response time, and R²=96.5%. These results showed that the independent variables of the two prediction models could explain the dependent variables. Using technology to keep oysters alive without water at ecological ice temperature may significantly prolong their survival time and maintain their quality. The model provides a theoretical basis for monitoring oyster activity in actual production.