This paper describes the usefulness of the group of multivariate techniques belonging to ordination for the analysis of ecotoxicological data sets. It is argued that although ecotoxicologists often gather multivariate data sets, they usually do not evaluate them with techniques that can handle multivariate data. Ordination techniques enable the researcher to extract an underlying structure out of a data set (eg. differences in composition of macro-invertebrate community between sites) and, if measured, relate this structure to explanatory variables (eg. concentrations of toxicants at the same sites). Five example data sets are presented to illustrate the underlying theory and the possibilities of ordination techniques. Two methods are presented, one based on weighted summation (eg. Principal Component Analysis, PCA) and one on weighted averaging (eg. Correspondence Analysis, CA). These techniques differ in the shape of the modelled response (linear versus unimodal) as the type of data they model (absolute versus relative). Results of these two methods are illustrated using a data set comprising levels of different PCB congeners measured in the blood of Adélie penguins in three periods. After this the constrained forms of PCA and CA are discussed, ie. constrained means that they are able to optimally display the differences in species composition (here levels of PCB congeners) due to explanatory variables (here period). Further examples illustrate the use of covariables, continuous and nominal explanatory variables, supplementary explanatory variables and forward selection of explanatory variables. Finally, two examples of Principal Response Curves (PRC) analyses are given. PRC is a technique that is especially developed to analyse time-series in which a control or reference is present. The PRC results are discussed for a designed experiment and a monitoring data set. The paper ends with a discussion focussing on the comparison between ordination techniques and other multivariate techniques used in the field of ecotoxicology.