The subject of the study is system-information models of processes and systems and their use for intelligent processing of information in production tasks. The use of intelligent information processing in production management systems is currently one of the key areas of development of informatics. The aim of the work is to develop system-information models of processes and systems for intelligent information processing allowing to analyze and solve production problems, in conditions of uncertainty. In the article the following tasks are solved: to analyze approaches to the definition of information characteristics of processes and systems; to develop the basis for modeling of system-information processes and systems for intelligent information processing; to develop system-information models and ways of their application for intelligent information processing in the tasks of production. The following methods are used: system-information approach to processes and systems; system-information modeling of processes and systems. The following results were obtained: the analysis of approaches to the definition of information characteristics of processes and systems; developed principles of modeling system-information processes and systems for intelligent processing of information; introduced the concepts of system information and information measure; developed system-information models and methods of their application for the intelligent processing of information in the tasks of production. Conclusions. The development of methods for solving various classes of practical problems using intelligent information processing is one of the key areas of research in computer science. The developed system-information models of processes and systems for intelligent information processing allow analyzing and solving problems. Thereby increase the efficiency of solving problems of analysis, synthesis and forecasting of production systems and technologies, as well as problems of production management. The system-information approach to processes and systems operates with new concepts – system information and information measure, it allowed developing system-information models for intelligent processing of information, as well as ways of their application at stages of product life cycle, which allowed solving problems of production. System-information models of processes and systems describe interaction between source and receiver on information level on the basis of sensitivity threshold. The communication channel between the source and the receiver of information operates, as a rule, under conditions of uncertainty, which can lead to the loss of information during transmission due to possible changes in the characteristics of the system. To describe their interaction, some models of intelligent information processing can be used, in particular, neural network models or fuzzy inference models. Their use will improve the efficiency of receiver state prediction, taking into account the state of the transmitter and the conditions of communication channel operation. The presented article has shown the relevance of developing system-information models for intelligent information processing at the levels of data reception, interpretation and communication, which allows expanding the class of solved production tasks.