In the past few years, several new phenotypes have been recorded in the Canadian dairy industry such as metabolic diseases and hoof health. With the addition of these novel traits, there are now a considerable number of traits considered for selection and over 80 traits are routinely evaluated by CDN. However, this quick increase in the number of traits has been done without a systematic estimation of the genetic correlations among traits. Not taking the genetic correlations into account can lead to a loss in selection efficiency, especially for traits with low heritability for which its relationship with another trait may have a large influence during the selection process. As part of the Efficient Dairy Genome Project (http://genomedairy.ualberta.ca) indexes for feed efficiency and methane emissions are in development, as well as their inclusion in the Canadian composite indexes (LPI and Pro$). As genetic correlations between these 2 new traits and the already evaluated ones will be needed, this is the proper time to look at the existing correlations among evaluated traits and estimate any missing ones. First, a selection of 35 of the 80 traits was performed. The first level of composite index rather than the individual index was taken for the conformation traits to avoid the multiplication of traits. As well, a few traits were discarded due to their nature of not being suitable for correlation estimation. Then, the Canadian literature was reviewed to fill the matrix of correlations. After this review, we found that correlations among traits within the same type of trait were mostly already calculated. However, there were few reported estimations of correlations between traits belonging to different groups of traits. We also identified some correlations that were calculated too far in the past and need to be re-evaluated. The next step will be the completion of the matrix with new estimations and the calculation of correlations with feed efficiency and methane emissions. This work is an opportunity to complete the knowledge of the Canadian traits, and the use of this new information will improve current and future dairy selection.