Objects classification is one of the applications which most efficaciously have been improved by deep learning, in the same way as other innumerable functions deeply pervading the modern society. In the present work we implement a deep learning framework with diffractive layers that collectively perform digit recognition. Neural networks constitute the computing system performing deep learning, which differs from any application of artificial intelligence – enabling machines to automatically learn from experience without being explicitly programmed – in that it creates the representations essential for classification organizing them into multiple levels. Our neural network is inspired by a framework recently introduced in the literature, termed as Diffractive Deep Neural Network (D2NN).