We study a family of robust nonparametric estimators for a regression function based on a kernel method when theregressors are functional random variables. We establish the almost complete convergence rate of these estimatorsunder the probability measure’s concentration property on small balls of of the functional variable. Simulations aregiven to show our estimator’s behavior and the prediction quality for functional data.