Ancherythroculter nigrocauda has been popular for the delicate texture of the meat, and is a proper material of processed food due to its flat shape. Salting is a key step in the processing of A. nigrocauda. In this study we aimed to optimize the conditions of the salting process, including reducing the salting time, lowering the salinity and improving the safety of the products, and hence to provide theoretical guides for the large-scale production. Using A. nigrocauda as the raw material, and the salinity and the total volatile basic nitrogen (TVB-N) as the indicators, we optimized parameters such as the salt concentration, the salting temperature and the salting time in single factor experiments. In these experiments, the salt concentrations were 3%, 5%, 7%, and 9%, the salting temperatures were 5℃, 10℃, 15℃, and 20℃, and the salting time was 24 h, 48 h, 72 h, and 96 h. Then the response surface methodology (based on the Box-Behnken experimental design principle) was used to optimize the salting process of A. nigrocauda. The response surface methodology analysis was adopted to build two second order quadratic equations between the salinity, TVB-N and salting conditions including the salt concentration, the salting temperature and the salting time. Taking the convenience into consideration, we set the optimal salting parameters as follows: salt concentration 4.5%, salting temperature 7℃, and salting time 38 h. Under these conditions, the salinity of the product was 3.23% and the total volatile basic nitrogen was 32.35 mg/100 g. The validating test showed that the actual results were very close to the predicted results from the corresponding second-order quadratic equations, thus the model may effectively predict the salt concentration and the TVB-N values of salted A. nigrocauda products. This technology could be applied to the large-scale production with reduced salting time, lower salinity, and improved food safety. Furthermore, it could also be employed in the salting process of other kinds of fresh water fishes.