In linear models and multivariate normal situations, prior information in linear inequality form may be encountered, or linear inequality hypotheses may be subjected to statistical tests. R package ic.infer has been developed to support inequality-constrained estimation and testing for such situations. This article gives an overview of the principles underlying inequality-constrained inference that are far less well-known than methods for unconstrained or equality-constrained models, and describes their implementation in the package.