Self-compaction concrete possesses non-segregation characteristics and the ability to flow through the heavily reinforced section with required viscosity. The addition of fibres in SCC enhances the strength of the concrete and reduces the brittle nature. Many such fibres like plant fibres, basalt, the glass was used in SCC as single reinforcement or hybrid reinforcement. This article focuses on the prediction of the strength of SCC infused with glass fibres. The input data was derived from various kinds of literature arranged in the format of nine input variables viz., cement, coarse and fine aggregate, water to powder ratio, superplasticizer, viscous modifying agent VMA, fly ash, GGBS/silica. A dataset of 128 samples collected was used to predict the output variables such as compressive strength and flexural strength of SCC with glass fibres. The mathematical modelling was deployed using ANN in MATLAB. The output of the developed model was assessed through RMSE (root mean square error) and R² (regression coefficient). It was concluded that the model can further be utilized to predict the strength (compressive and flexural) of SCC concrete

Keywords: Self-compaction concrete, fibre, glass, Artificial Neural Network ANN, MATLAB