Eggshell concrete is an innovative green material that helps to recycle eggshell waste while reducing the environmental harm caused by excessive cement production. However, recent studies on eggshell concrete are limited, and the outcomes may vary due to the variation of mix design. The design of the experiment is used to simplify and optimize the study of sustainable concrete, yet analysis involving eggshell concrete is still scarce. This paper aimed to develop mathematical models for the prediction of eggshell concrete compressive strength using mixed regression (MR) and response surface methodology (RSM). Overall, 43 datasets were collected from available studies in the literature on eggshell powder as partial cement replacement. The input variables used were the percentage of eggshell, percentage of Ground Granulated Blast-furnace Slag (GGBS), cement content, fine aggregate, coarse aggregate, water, and Conplast SP-430 superplasticizer. The analysis of the contour plot concluded that eggshell powder increased the concrete compressive strength at an optimal replacement percentage between 5% and 10%. However, the partial cement replacement with eggshell powder is more optimal for mix design with higher water content. The statistical results of the model, such as R2, adjusted R2, and root-mean-square error (RMSE), indicated that both MR and RSM models are powerful tools to formulate and predict the eggshell concrete compressive strength. However, RSM models showed better accuracy and lower deviation.
