Solid acid catalysts are an important class of catalysts because of their applications in various organic reactions. A 12-tungstophosphoric acid (TPA) is a member of heteropoly acid (HPA) compounds, which grabbed attention because of its low volatility, low corrosivity, higher activity, and acidity compared to sulfuric acid. However, the major problems of using TPA are its solubility in polar media, and its lower surface area. Therefore, various techniques are applied to use it as heterogeneous catalysts. Biodiesel is a diesel substitute renewable fuel, which is produced from various renewable feedstocks through transesterification or esterification reactions. Acid catalysts can catalyze both transesterification and esterification reactions. For this reason, research has been conducted to study the catalytic activity of various TPA precursory solid acid catalysts for biodiesel production. In this Review, a data mining technique has been applied to extract valuable information from the previously published literature. For this purpose, an artificial neural network (ANN) model has been developed based on the published research data to capture the general trends or to make predictions. Both catalyst properties and reaction conditions are trended and predicted using the network model.