A nonparametric model based on B-Splines and a cross-validation criterion for hyperparameter selection are given for modal regression. The existing nonparametric local polynomial modal regression performs well in the goodness of fit, but with a high computational complexity. Owing to the nice properties of B-Splines, modal regression based on B-Splines performs comparably with the local polynomial modal regression on estimation but spends much less computational burden. Furthermore, because the commonly used cross-validation hyperparameter selection criteria are not suitable to modal regression, we construct a new cross-validation hyperparameter selection criterion. Simulations and application show that this criterion behaves well for modal regression.