This paper predicts the compressive strength of reinforced cement concrete with different pozzolan having different biproducts such as flyash, GGBS, silica fumes and rice husk on 28 days with multiple regression analysis (MRA) and artificial neural network (ANN) and compares them. The model prepared uses the data from the previously published papers; the data collected from the papers are cement content, coarse aggregate, fine aggregate, water/cement ratio, replacement of cement with pozzolan materials like GGBS, flyash, silica fumes, rice husks, SiO2 , Al2O3, Fe2O3, CaO, MgO, SO3 quantities are taken in the form of input for the models and the respective compressive strength obtained from the literature is taken as the target strength or parameter. The result shows that this the model made with these parameters produces a valid model through MRA and ANN. © 2021 Institute of Physics Publishing. All rights reserved.