Reproductive performance of lactating dairy cows influences the annual calving frequency, replacement heifers available, and milk yield. The goal of this study was to estimate the genetic parameters of fertility indicators in dairy cattle. Measurements from 953 Holstein cows from one farm in Texas across 2 calving years were analyzed. Three fertility indicators were evaluated: probability of cycling at d45 post-calving (Pr_Cyc), probability of disease diagnosis at 45d post-calving (Pr_Sck), and probability of pregnancy after 2 AIs (Pr_Prg). These indicators were estimated using a logistic model including the covariables: dystocia, retained placenta, body condition score at 7d and 35d post-calving (BCS7 and BCS35, respectively), and blood β-hydroxybutyrate (BHBA) indication of subclinical ketosis. Univariate sire models including the effects of contemporary group and lactation number were used to estimate the genetic parameters of days open (DO), BCS7, BCS35, Pr_Cyc, Pr_Sck, and Pr_Prg. The percentage of cows cycling, diagnosed with a disease, and pregnant after 2 AIs were 69.7%, 14.9%, and 64.6%, respectively. The marginal probabilities indicated that cows diagnosed with dystocia, retained placenta, metritis, and mastitis were 1.7%, 6.0%, 11.4%, and 7.3% less likely to be cycling than healthy cows, respectively. Cows were 2.7% and 4% less likely to be cycling per unit increase in mucus score and BHBA, respectively. The heritability estimates (and standard errors) for Pr_Cyc, Pr_Sck, Pr_Prg, DO, BCS7, and BCS35 were 0.23 (0.15), 0.29(0.17), 0.58(0.19), 0.19(0.13), 0.25(0.16), and 0.25(0.18), respectively. Our results indicate that the fertility traits considered in this study have an important genetic component and that they could be used as effective indicators of fertility in breeding and management decisions. These findings could be the foundation to develop novel fertility indices that combine the fertility indicators hereby studied to improve the accuracy of pregnancy prediction and selection for improved fertility in dairy production. These findings contribute to a long-term multistate project database (USDA-NIFA-AFRI-003542) for direct measures of fertility.