Abstract Finding a solution to the problem of the large buildup of coal ashes is a vital necessity. Although the use of coal ashes in fired clay bricks has been thoroughly investigated, there is insufficient information on their industrial utilization and researchers do not agree on whether or not this addition improves the quality of the final products. Therefore, a database has gathered 20 years of research containing key factors related to the quality of the bricks (i.e., chemical composition, firing temperature, soaking time, open porosity, water absorption and compressive strength). Then, random forest regression and artificial neural networks (ANN) modeling were used to separately predict the parameters concerning the quality of the final products. The overall conclusions were that the compressive strengths were the highest when using fly ashes and that class F ashes were highly suitable to be used in the brick industry as a replacement material for brick clay. In addition, the ANN models showed higher coefficients of determination and an overall better fit to the experimental data. By changing the chemical makeup of the initial materials and their proportions, the particle size of the ashes, the firing temperature and soaking time, as well as the size of a product, the created models can be used to estimate the quality of the brick containing coal ash. That is crucial because the inconsistent chemical composition of ash is generally the main obstacle to its utilization. The local sensitivity analysis revealed the highest influence of the content of the alkali oxides in the initial clay on the fired clay bricks due to their fluxing effect. In the case of ash-clay bricks, the decisive factors were the type of furnace used, the ashes’ class, the Na₂O content in raw clay, and the K₂O introduced with the ash. The F class ashes containing about 2–3% of K₂O and <5% of CaO gave the highest compressive strength in bricks fired at 1000–1100 °C.

Additional analyzes were made for 50% pond ash and 50% clay bricks to test the best-suited model and fill in the knowledge gap. The results obtained in this study are important for supporting the decision in the selection of materials and process parameter values that will increase the quality of the ash-clay-fired bricks.