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Simple Summary: The study aimed to estimate growth curves and genetic parameters for Nellore cattle using a random regression methodology. The dataset included 6974 calves raised in Pantanal, MS, Brazil, and 53,233 weight records, with at least four weighings per individual. The model considered direct and maternal genetic additive effects and maternal permanent environmental effects at random. Cubic orthogonal Legendre polynomials were used to fit the growth curve, with fixed effects of sex, year of birth, farm, calf birth month, and cow age at calving. The mean weights at 120 and 205 days were 93.43 kg and 180.42 kg, respectively. Animals born in the dry season had higher average weights, leading to higher weights at 646 days. Direct heritabilities ranged from 0.35 to 0.75, while maternal heritabilities were low (0.03 to 0.08). Random regression effectively adjusts growth curves and aids in selecting superior animals for breeding. The objective was to estimate the growth curves and genetic parameters using random regression methodology for Nellore cattle raised in Pantanal, MS, Brazil (6974 calves; n = 53,233 weights), with at least four weighings per individual. The model considered direct and maternal genetic additives and maternal permanent environmental effects at random. Orthogonal Legendre polynomials of cubic order were used to fit the growth curve. Analyses of variance were performed using the GLM procedure. The model used contained the fixed effects of sex, year of birth, farm, and the covariates calf birth month (linear and quadratic) and cow age at calving (linear and quadratic). The adjusted mean weight at 120 days of age was 93.43 ± 19.78 kg, and for 205 days of age, it was 180.42 ± 26.58 kg. Animals born in the dry season had a higher average weight [kg] (219.57 vs. 211.78, 3.7% higher) and, consequently, had higher weights at 646 days of age. Estimates of direct heritabilities (h2a) ranged from 0.35 to 0.75 (high magnitudes), and maternal heritabilities (h2m) along the trajectory of low magnitudes ranged from 0.03 to 0.08, respectively. The use of random regression to evaluate beef animals allows for adjusting the growth curve and selecting the best animals to be the parents of future generations. [ABSTRACT FROM AUTHOR]