This work addresses an efficient neural network (NN) representation for the phase-field modeling of isotropic brittle fracture. In recent years, data-driven approaches, such as networks, have become active research field in mechanics. this contribution, deep networks—in particular, feed-forward (FFNN)—are utilized directly development failure model. The verification and generalization trained m...