Accurate and cost-effective approaches are required to determine the unsaturated soil property functions. Past research studies have indicated that particle-size distribution data of soils are a fundamental and beneficial aspect in this domain. By comprehending the particle-size distribution data of soils, one can estimate the behavior of unsaturated soils with greater accuracy and precision. For the present investigation, an exhaustive examination of the literature was carried out first, followed by a comparative analysis of the PSD curve fitting capability of various models that are presently available. The performance of two such models, namely MFU -(2009) and ATU - (2014), was meticulously scrutinized by employing thirty-four PSD data of fine-grained soils. The PSD curve fitting model that offers an efficient curve fitting performance was chosen by means of comparing a multitude of statistically goodness fitting measures. Through a comprehensive analysis of the literature and comparative studies of preexisting models, an improved unimodal PSD curve fitting model has been proposed and verified for the fitting of thirty-four PSD data of fine-grained soils. Based on a thorough examination of literature and a comparative analysis of existing PSD curve fitting models, it has been determined and validated that the PSD curve fitting model proposed by ATU et al. in 2014 is the suitable for accurately fitting the PSD curve of fine-grained soils better was proposed Moreover, the study made in this research was to improve the curve fitting performance of ATU and et al - (2014) PSD curve fitting model lead a new improved four parameter PSD curve fitting model capable for fitting the PSD data of fine-grained soil. Consequently, the parametric study on the new proposed PSD curve fitting model parameters are made and reasonable and meaningful descriptive PSD curve that can be used for the study on unsaturated soil mechanics is proposed. Keywords: Unsaturated Soil, Unimodal, Curve Fitting.