The laplace package provides methods for applying Laplace approximations to entire neural networks, subnetworks, or just the last layer. It facilitates posterior approximations, marginal-likelihood estimation, and posterior predictive computations for deep learning models. The library supports various hessian factorizations, prior precision tuning methods, and predictive approaches, making Bayesian deep learning more accessible through a well-documented Python API.