The objective of this study was to develop growth prediction models of Listeria monocytogenes in salmon under fluctuating temperatures. A three-strain cocktail of Listeria monocytogenes isolated from salmon was inoculated to sterile salmon to perform dynamic(1-35 ℃) studies. The growth data collected from 3 independent temperature profiles were used to determine the kinetic parameters and construct a growth model combining the primary model (Huang Baranyi and Two-compartment model) and secondary model (HSR model) using a one-step kinetic analysis method. The results showed that Huang-HSR model， Baranyi-HSR model and Two-compartment-HSR model had an equal goodness of fit. The minimum growth temperature of Listeria monocytogenes estimated by the above three models were 0.51， 1.21 ℃ and 1.20 ℃， respectively， and the maximum growth concentration were 9.41， 9.35， 9.36 lg (CFU/g). Based on the definition of the lag time in models and the conciseness of models expression， Huang-HSR model was suggested to describe the growth of Listeria monocytogenes in salmon. Huang-HSR model was then validated by the newly designed dynamic growth experiments and isothermal growth data from literature. The RMSE calculated by Huang-HSR model was both between 0.29-0.59 lg (CFU/g) under dynamic conditions； while the RMSE was between 0.28-0.85 lg (CFU/g) for the model under constant temperatures， indicating Huang-HSR model can be used to describe the growth behavior of Listeria monocytogenes in salmon. The models were then used to simulate the growth of Listeria monocytogenes under a variety of continuous sine-wave temperature profiles to demonstrate its potential application. The mathematical models developed in this study can be used to predict the dynamic growth of Listeria monocytogenes in salmon under fluctuating temperatures.