The issues that the construction sector currently faces with regard to productivity and efficiency are well acknowledged. In the construction industry, there is plenty of space for efficiency to improve, with an increasing number of new tools and methods coming out. One of the solutions to increase efficiency is the application of modern methods of construction. The modern methods of construction, especially dry construction techniques, are developing so that there is a larger volume of high-quality production with a shorter time for procurement. Not only in the construction of skeletons but also in the finishing works, it is a huge advantage if there are implemented techniques that eliminate traditional wet construction works and thus shorten the construction time. On the other hand, however, the question of efficiency in relation to their costs is raised. Based on theoretical and empirical research, the aim of this study is to demonstrate the potential of modern dry construction systems and solutions for finishing works, especially in relation to the construction time and construction cost. For this purpose, an expert knowledge system, named the complex COMBINATOR, was developed. Through a set of simulations with the help of the COMBINATOR, the effects of different combinations of dry construction systems and techniques (DCSTs) and traditional wet construction systems and techniques (WCSTs) on the time and cost of finishing construction works were measured. Based on the results of simulations carried out through the complex COMBINATOR with an inference engine that enabled these simulations, the potential of dry construction techniques for the implementation of finishing works in the construction of residential buildings was demonstrated. Without simulating the effects of the individual technological models for finishing construction works in relation to two of the most important parameters of construction projects, namely time and cost, it would not be possible to obtain the resulting parameters for different combinations of DCSTs and WCSTs from the study presented. Therein lies the huge importance of the presented knowledge system for deciding on the benefits of DCSTs.