Eleven data points were selected from Nascimento et al. for this evaluation, as it assesses the FP prediction of ethyl biodiesel, binary, and ternary fatty acid ester mixtures, using UNIFAC models to quantify the mixture's non-ideal behavior. Seven of these points corresponded to ethyl decanoate and ethyl stearate mixture, and four to different biodiesel types. The model deviation for biodiesel and binary mixtures was then compared with the deviation of the neural network model for the same dataset, as presented in Tables and, respectively. The results showed that the neural network model performed better compared with the UNIFAC models for the biodiesels. However, for the binary mixture, the model did not show accuracy as high as before but maintained a reasonable prediction. This discrepancy can be attributed to the limited training data, which negatively affected the model's performance due to its purely data-driven nature.