The relative performance of genotypes for yield and agronomic traits is measured in multi-environment trials (METs) in order to predict their performance in a target population of environments (TPE). It is shown that it is the correlation of genotype performance between environments that allows such a prediction. Thus, efficiency of selection and size of realised genetic advance in the TPE depend on the genetic correlation between the test and target environments, the heritability in the test and target environments and the phenotypic variance in the target environments. The phenotypic correlation between genotype performance in test and target environments estimates the combined effects of the genetic correlation and heritability parameters. These relationships from correlated genetic advance theory can be applied to various forms of retrospective analysis (cumulative analysis over years, sequential analysis by adding one year’s data at a time, and status analysis by embedding this year’s data in a long term discrimination space) used to analyse MET data. The best estimate of genotype performance to use in these analyses is obtained using the approach of Gilmour, Cullis and Verbyla (JABES 2:269-293, 1997). One should fit a model combining design information and spatial adjustment within the trials, either in a one-stage analysis or, if that is not possible, a two-stage analysis where each individual trial is weighted according to the inverse of its estimated error variance and number of replicates