This study aimed to examine the phenotypic variation observed in fine milk components, the use of mid-infrared (MIR) spectroscopy to predict these components, and the correlations with other milk production traits. A total of 4116 milk samples were collected from 414 dairy cows from 44 Canadian herds. Overall 3117 samples were analyzed for casein micelle size, 986 and 937 for total and soluble calcium, respectively, and 2054 for lactoferrin. Individual milk MIR spectra were obtained. Linear mixed models with repeated records were used to test the effects of herd nested within breed, breed, days in milk class, parity, and season on milk components. Lactoferrin content in milk increased with stage of lactation and parity number. Prediction equations were developed by partial least squares regression to predict each milk component using MIR spectroscopy, with the greatest coefficient of determination achieved for lactoferrin (0.55). Pearson correlation coefficients for lactoferrin with somatic cell score and protein percentage were 0.49% and 0.40%, respectively. The estimated correlation increased to 0.53% for predicted lactoferrin and protein percentage. The examined fine milk components exhibited variation, but low accuracies for their MIR prediction may limit the utility of this technology for their phenotyping.