<p>The scientific community has determined that the soil water characteristics curve (SWCC) is the most significant soil feature when dealing with unsaturated soil mechanics. Practitioners find this soil feature unappealing because laboratory testing requires considerable time. Extensive laboratory studies measure the soil parameters for the unsaturated soil constitutive models. Thus, empirical methods for assessing the characteristics of unsaturated soil would be beneficial. To address this, the study aims to develop a prediction model for simplifying SWCC model fitting parameters by correlating them with basic soil properties. This study collected fourteen red clay soil samples from test pits in Debre Markos city, Ethiopia and conducted compaction testing, basic soil property testing, and pressure plate tests to determine SWCC discrete data points. Regression models were used to determine the relationship between SWCC model fitting parameters and basic soil properties. The study measured SWCC for the red clay soils using the pressure plate test and performed regression analysis using the SAS JMP®Pro-14 statistical software package. A statistically simple regression model for SWCC model fitting parameters such as a_f, n_f, m_f, and residual suction was developed. The equations presented in this paper predict the SWCC of soils without actual SWCC testing. They can easily be incorporated into computer codes to solve various unsaturated soil mechanics problems. A cross-validation technique was employed to validate the developed prediction model, and the models showed excellent correlation with the basic soil property test results. Furthermore, the developed predictive model was validated using the models taken from the literature.</p>