Concrete might be exposed to high temperatures caused by fire that adversely affect its mechanical properties. Therefore, the ability to predict the mechanical properties of concrete exposed to high temperatures is necessary. In this study, Artificial Neural Network (ANN) models were developed to assess the mechanical properties of concrete exposed to high temperatures. For this purpose, 728 experimental results were collected from the available literature to predict mechanical properties of concrete at high temperatures, including compressive strength, tensile strength, and modulus of elasticity. The input database contains the volumes of coarse aggregate, fine aggregate, water, cement, water-cement ratio, coarse aggregate type, percentage of supplementary cementitious materials as the cement replacement, temperatures, and test methods. The mechanical properties were defined as the output variable. Proposed models are in good agreement with the experimental data and can predict the mechanical properties of concrete exposed to high temperatures.