<p dir="ltr">In this dissertation, we investigated the genetic background of milk consumption, feeding behavior, disease resistance, and calf resilience in North American Holstein dairy calves using precision livestock farming (PLF) technologies and genetic modeling. Genomic and phenotypic information obtained from automatic milk feeding machines were obtained from 10,072 pre-weaned Holstein calves and used to derive and genetically evaluate novel traits such as daily milk consumption, calf resilience, and incidence of bovine respiratory disease (BRD). Heritability estimates for milk consumption and feeding behavior traits were found to be low but improved with specific statistical models, suggesting potential for genetic improvement if included in selection schemes. Random regression models captured greater amounts of genetic variability among calves for longitudinal milk feeding and behavior traits, with moderate negative (favorable) genetic correlations between milk consumption and BRD, indicating potential for genetic selection to enhance calf health outcomes and performance based on milk intake data. Various quantitative trait loci (QTL) for milk consumption, drinking duration traits, feeding behavior, and disease susceptibility were identified, linking key genes involved in metabolic processes, growth, and overall health. The same datasets were used to derive resilience indicators based on cumulative milk consumption. Genetic parameters for resilience traits, including amplitude, perturbation time, and recovery time, were estimated, highlighting substantial phenotypic and genetic variability. Significant genomic regions for six resilience traits were identified, with key genes such as <i>ABCB8</i>,<i> ABCF2</i>, and <i>AGAP3</i> linked to resilience traits, impacting mitochondrial function, cellular stress responses, and homeostasis. Pathway analyses revealed critical biological processes for stress response, including nucleotide binding and hormone activity. Genes such as <i>EPC1</i>, <i>ASB10</i>, and <i>ASIC3</i> were associated with recovery time, while <i>DPP6</i>, <i>GBX1</i>, and <i>GIMAP5</i> were linked to other resilience traits. These findings underscore the importance of genetic tools and breeding strategies in enhancing health, resilience, and productivity, offering potential new traits to genetically improve health and resilience in dairy cattle, and consequently, improve the sustainability of the dairy cattle industry.</p>