Prediction of FRP-concrete interfacial bond strength based on machine learning

•Established a database with 1375 FRP-concrete direct shear test specimens.•Analyzing the correlation of six variables revealed that five factors affecting the FRP-concrete interfacial shear capacity most.•Six machine learning models substantially increased the prediction accuracy compared with the sixteen traditional empirical equations, and they especially reduced the variation.•Based on the ANN algorithm, an accurate, explicit and practical equation was derived to predict the FRP-concrete interfacial shear capacity.