Concrete is one of the most widely used construction materials, and in recent days, thrust is being given to produce concrete in a sustainable manner. Concrete strength is one of the important parameters that decides the durability of structures, and it is being evaluated mostly by destructive testing in the laboratory which is not only costly but also time consuming. Numerous methods were developed by researchers across the globe to predict concrete strength using limited data; in this work, we had made an attempt to predict sustainable concrete strength using autoregressive integrated moving average (ARIMA) model. The ARIMA model (with expert modeler) coefficients are described as ARIMA (0,1,14). The study uses ARIMA model with expert modeller to choose the most significant variables that Box and Jenkins used to build a prediction model in SPSS that can estimate CS, mass, NDT of concrete results. The results reveal that the best ARIMA model can be formulized as ARIMA (0,1,14). This kind of analysis and implications of ARIMA models and fitting procedures are useful in forecasting results of compressive strength, mass, and NDT results.