In conditions of keencompetition in the markets for goods and services, a huge emphasis is put on the stages of subject-wise planning, issuing design specification, and front-end engineering designwhen manufacturing new products. These stages are primarily responsible for the key technical and economic products’ characteristics that directly identify the product conceptual design and marketability. Current information and analytical systems (IAS)that dictate a choice of perspective directions to develop newly created products and their most preferred specimens basically use knowledge of experts about the value of estimation indicators. The latter usually serve as a basis for opting the best specimens of the newly designed technical systems. Evaluation of quality and technical level (TL) of complex technical systems using the created IAS often involves value functions (for instance, Fishburn function), which imply that a dialogue with a decision-maker (DM) produces information about his views of “value systems” or “preference systems”, used to construct value functions. Developers of new products experience considerable difficulties in choosing a value function of estimation indicators when working with IAS. The paper proposes to determine a value function for numerical indicators using the newly designed information model, based on expert estimations consistent with estimation of truck TL. A technical device and algorithm to determine value functions of unit estimation CTS indicators were developed according to the method. An invention was registered, and a patent was issued. The method also implies taking random factors into account when evaluating CTS TL for, as an example, “reliability” as the key estimation indicator.Two patents of the Russian Federation were obtained for invention of a time digitizer and a device for estimating effectiveness of various systems through sampling random values. The suggested method of generating a value function enables a scientist to choose the type and nature of a value function that will allow to increase the degree of CTS TL evaluation reliability, and optimize the cost of obtaining initial information when predicting CTS reliability due to evaluation of adaptive digitalizationof random processes initiated in IAS. The paper materials may be of service to designers of complex systems at the initial stages of developing thereof in evaluating possible alternatives of CTS implementation, and determining TL at all stages of CTS life cycle.