This chapter focuses on the tools and techniques that have been developed for querying 3D model collections using another 3D model as a query. The chapter describes the different datasets and benchmarks, which are currently available in the public domain. It presents the metrics used to evaluate the quality and performance of a 3D retrieval algorithm. Retrieval algorithms are based on similarity search, i.e. they compute the similarity of the query's descriptor to the descriptors of the models in the database. The chapter discusses three classes of methods used to compute such similarity. The first class of methods use standard distance measures. The second class of methods use Hamming distances on hash codes. The final class of methods use manifold ranking techniques. The use of global descriptors for 3D shape retrieval is relatively straightforward. A table summarizes and compares the performance of some global descriptors.