The aim of this study was to estimate genetic parameters for female fertility and production traits in first-parity Czech Holstein cows and to quantify the effect of using this information on the accuracy of a selection index in seven different scenarios. In order to estimate genetic (co)variance components, the DMU software running an AI-REML algorithm was used. The analyses were made using a series of bivariate animal models. The pedigree included 164 125 animals and it was set up using a pruned animal model design. The present study included the following female fertility traits for the first lactations: calving to the first insemination (CF), days open (DO), calving from the first to the last insemination (FL), and milk production traits: milk production (MLK), kg of fat (FAT), and kg of protein (PROT). The heritability for all the investigated fertility traits was low and close to 0. Moderate heritabilities for production traits ranging from 0.20 (MLK) to 0.23 (PROT) were estimated. The strongest unfavourable correlation was found between PROT and DO (0.49). Other estimated correlations between fertility traits and production traits were moderate, ranging from 0.26 to 0.41. The results of this study evidence that cows with the poorest genetic potential for reproductive performance are those having high genetic potential for milk production and milk components. The results also show that the number of days from calving to new pregnancy depends on the production level. Seven investigated scenarios using selection index theory show a clear trend for increasing accuracy when more fertility traits were added as well as when higher numbers of daughters with information on reproduction traits per sire were available