The system for classification and separation of a fish successfully developed within this paper is the basis for stronger automation of the fish processing industry. The industry in which, to date, there are mostly processing lines with a very high level of human labor represents a huge potential for more intense automation. At the same time, the challenges of automating fish processing lines limit the stronger presence of such systems. Increasing economic pressures on producers of fish products represent a kind of a trigger in the process of transformation from a predominantly manual production system to a robotic one. The industrial vision system, artificial intelligence, and the robotic manipulator are the three key segments of the system elaborated in this paper. These system segments successfully classify and separate sardines mixed with anchovies on the conveyor belt. Classification is performed by machine learning methods based on data obtained from the vision system. Image processing and machine learning methods are implemented on a computer which, in turn, is connected to a robotic manipulator. The delta robot, which performs the separation itself, was chosen because of the very short cycle times and has the ability to track the object on the conveyor in motion. Based on the information it receives from the computer, the robot excludes, orients, and palletizes sardines from the conveyor belt. Once palletized, the fish is ready for further processing in the production line. The maximum flow of fish through the developed system is relatively large and this feature, along with the fact that the system is very easily upgraded with multiple robots, is a proof of the concept.