## 1 Introduction
[PERSON] and [PERSON] (2017) used factor analysis as a part of the study to assess the risk of failure on rock slopes. [PERSON] et al. (2018) reduced the variable size and found out the interrelations for rock mass classification. [PERSON] and [PERSON] (2019) utilized factor analysis to determine the interrelations of variables to develop an equation of unconfined compressive strength for rocks. [PERSON] et al. (2019) reduced the number of rock properties to derive the geomechanical zonation of a mine. However, these above-mentioned studies performed their research by applying factor analysis as a part of their study. Considering these, the following studies were achieved by integrating the factor analysis as the main methodology. For example, the prediction of the desired soil properties was demonstrated by [PERSON] (2018), [PERSON] et al. (2019), and [PERSON] (2020) who developed a statistical model by using the factor analysis to predict dry density, water saturation, and water content of soil stratum, respectively. [PERSON] and [PERSON] (2018) investigated the ways and effectiveness of the remote measurement of swelling potential of soils using factor analysis. Another direct use of factor analysis is for classification, indexing, and ranking purposes. [PERSON] et al. (2018) derived a model to prepare landslide hazard maps. [PERSON] and [PERSON] (2018) prepared soil swelling potential maps by characterizing the expansive soils by factor analysis. [PERSON] (2018) utilized factor analysis to create geotechnical maps for land management. [PERSON] et al. (2018) and [PERSON] et al. (2018) ranked and classified debris flow zones and created landslide susceptibility maps by utilizing the factor analysis, respectively. Considering the literature above, this study demonstrates a simple yet powerful use of factor analysis as the main methodology in the Geotechnical Engineering discipline. In this study, many different properties of soil samples were gathered from the geotechnical literature of Cyprus. Strong relation was searched between these properties and the PI. Considering only the correlated properties, exploratory factor analysis was performed to reduce the number of variables and discover the interrelations between these properties. Confirmatory factor analysis was carried out to test the theory of underlying relations on specifically chosen soil properties. After the data reduction, factor scores were assigned to individual soils which distinguished the plasticity characteristics of the soils. These factor scores were weighted, summed, and standardized to identify a model to represent overall plasticity potential of each soil. The analysis shows an improvement in correlations between some soil properties and this model that are weaker when only based on PI. The overall ranking of soils based on plasticity index was changed when compared with this model. Sand content was incorporated later into the model and a nonlinear expression is defined. A measurement of the unified plasticity potential of soils is proposed through the use of a single equation. The model is divided into six divisions based on the plasticity potential. Considering these reasons, the use of this model was found more representative in practical applications, as it became evident that PI solely might need refinement for practical use.