Models which ensure accurate non-destructive estimates of the freshness of fish meat（K-value）in real time are proposed to improve quality control and maintain the skill level of distributers of marine products. Six kinds of fish, each differing with respect to the hue of the fish body surface, were used to construct the models. Relationships between fish coloration and K-values from sample acquisition until 72 hours later under refrigeration at －２℃, +２℃, and +６℃ were investigated. A statistical analysis revealed that fish coloration does reflect its K-value, although the strength of the relationship differs by fish species. Three models were designed on the basis of these results, and the usefulness of each model was evaluated. The models are as follows:（1）Model to estimate the K-value of fish meat based on the coloration of the fish body surface（Model 1),（2）Model to predict the K-value of fish meat after several hours for the same fish for which the K-value was estimated with Model 1（Model 2), and（3）Model to predict the K-value of the fish meat after an arbitrary elapsed time for just-killed fish（Model 3). For all three models, a high estimation accuracy was confirmed, demonstrating their potential usefulness for quality control in the distribution of marine products.