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Abstract: The development of technological readiness is one of the key conditions for the training of future civil engineers. Effective modernization of the education system, capable of preparing competitive specialists, involves the search for the effective mean to predict students’ knowledge gaps. The goal of the study is to create the model of the “average” student of civil engineering educational institution by EDM tools. Previously, the modeling of the “average” construction student by means of EDM has not yet been carried out. First of all, in order to achieve this goal, there was an attempt to determine the average level of the “average student” of the construction training institute without resorting to statistical processing of empirical data. The paper provides an example of modeling the “average student” studying in the construction educational institution using the Data Mining and Visual Mining tools. The grades of the students from 5 academic groups of the Civil Engineering Faculty at the State Educational Institution of Higher Professional Education “Donbas National Academy of Civil Engineering and Architecture” were taken as initial data. The results of visualization of students' rating points are presented. It is more effective means of assessing students’ average results than statistical processing. It is proved that the productivity of the educational results of the future civil engineers depends on the students’ achievements in the “most difficult” subject in the discipline in which most students experience difficulties. The subjects have the strongest influence on the average mark of the certificate: “Resistance of materials” and “Theoretical framework of heat engineering” are determined. Using the graphical capabilities of the Statistica program, it was visualized the surface characterizing the probability of the students getting a high average mark with the successful passing of “complex” disciplines. It will help develop recommendations for increasing the number of successful students.