The modern stage of the agro-industrial complex is characterized by an increasing complexity, intensification of technological processes of complex processing of materials of animal origin also the need for a systematic analysis of the variety of determining factors and relationships between them, complexity of the objective function of product quality and severe restrictions on technological regimes. One of the main tasks that face the employees of the enterprises of the agro-industrial complex, which are engaged in processing biotechnological raw materials, is the further organizational improvement of work at all stages of the food chain, besides an increase in the production volume. The meat industry as a part of the agro-industrial complex has to use the biological raw materials with maximum efficiency, while reducing and even eliminating losses at all stages of processing; rationally use raw material when selecting a type of processing products; steadily increase quality, biological and food value of products; broaden the assortment of manufactured products in order to satisfy increasing consumer requirements and extend the market for their realization in the conditions of uncertainty of external environment, due to the uneven receipt of raw materials, variations in its properties and parameters, limited time sales and fluctuations in demand for products. The challenges facing the meat industry cannot be solved without changes to the strategy for scientific and technological development of the industry. To achieve these tasks, it is necessary to use the prediction as a method of constant improvement of all technological processes and their performance under the rational and optimal regimes, while constantly controlling quality of raw material, semi-prepared products and finished products at all stages of the technological processing by the physico-chemical, physico-mechanical (rheological), microbiological and organoleptic methods. The paper presents the man methods and approaches to prediction in the meat industry.

prediction, predictive methods, factographic methods, expert methods, combined methods, biological raw materials, rheological methods, mathematical modeling, simulation modeling, foresight method

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