Solid fat content (SFC) is a fundamental physico-chemical property of lipids. Common SFC determination methods are time-consuming and expensive. Here, regression models were used for description of the SFC of chemically interesterified palm stearin/soyabean oil blends as a function of fatty acid composition, temperature or both. Briefly, sigmoidal models described the SFC curves as a dependent variable of saturated fatty acids (SFA) very well [SFCf(SFA), R²>0.98, mean absolute error (MAE)<1.71%] or temperature [SFCf(T), R²>0.98, MAE<1.67%]. However, the Gompertz function predicted the SFCf(SFA) and SFCf(T) curves better than the other functions. Lastly, a Gompertz function describing SFC as a multiple function of both SFA and temperature [SFCf(T,SFA)] was developed, which could describe the experimental data with R2=0.98 and MAE=1.86%. Validation of the Gompertz SFCf(SFA) and SFCf(T,SFA) models confirmed their high ability in prediction of SFC of different interesterified fats made from fully hydrogenated soyabean oil, palm stearin or palm olein.