Flexural strength is a measure of tensile strength of concrete beams or slabs. Concrete is generally used as construction material. The use of huge quantity of natural fine aggregate (NFA) and cement in civil construction work has given rise to various ecological problems. The industrial waste like Blast furnace slag (GGBFS), fly ash, metakaolin, silica fume can be used as partly replacement for cement and slag sand obtained from crusher, was partly used as fine aggregate. In this work, MATLAB software model is developed using neural network toolbox to predict the flexural strength of concrete made by using pozzolanic materials and partly replacing natural fine aggregate (NFA) by slag sand. Due to the replacement of the Pozzolanic material and fine aggregate the strength properties are achieved. Artificial Neural Networks (ANN) is used to predict the strength properties. Flexural strength was experimentally calculated by casting beams specimens and results obtained from experiment were used to develop the artificial neural network (ANN) model. ANN has three layers which include output, input and hidden layer. The input layer consists of the quantity of cement, course aggregate, water content, percentage of Metakaolin and steel slag sand. The output consists of compressive strength of concrete. While developing ANN model 50 samples are used as training testing data sets. Two assessments are carried out one is to determine the effective number of neurons in the hidden layer for predicting the network system and second is to evaluate the accuracy of predicted network is done under different load conditions. Generally Artificial neural network learns from training and gives extremely good results. ANN can be used to escalate the experimental data to determine the flexural strength of concrete obtained from partly replacing cement with pozzolans and natural fine aggregate (NFA) by slag sand. High accuracy outcomes are observed when compared with the experimental results and results obtained after training of neural network