Myosin heavy chain (MyHC) type and muscle fiber size are informative but time-consuming variables of interest for livestock growth, muscle biology, and meat science. The objective of this study was to validate a semiautomated protocol for determining MyHC type and size of muscle fibers. Muscle fibers obtained from the longissimus and semitendinosus of fed beef carcasses were embedded and frozen within 45 min of harvest. Immunohistochemistry was used to distinguish MyHC type I, IIA, and IIX proteins, dystrophin, and nuclei in transverse sections of frozen muscle samples. Stained muscle cross sections were imaged and analyzed using two workflows: 1) Nikon workflow which used Nikon Eclipse inverted microscope and NIS Elements software and 2) Cytation5 workflow consisting of Agilent BioTek Cytation5 imaging reader and Gen5 software. With the Cytation5 workflow, approximately 6 times more muscle fibers were evaluated compared to the Nikon workflow within both the longissimus (P < 0.01; 768 vs. 129 fibers evaluated) and semitendinosus (P < 0.01; 593 vs. 96 fibers evaluated). Combined imaging and analysis took approximately 1 h per sample with the Nikon workflow and 10 min with the Cytation5 workflow. When muscle fibers were evaluated by the objective thresholds of the Cytation5 workflow, a greater proportion of fibers were classified as glycolytic MyHC types, regardless of muscle (P < 0.01). Overall mean myofiber cross-sectional area was 14% smaller (P < 0.01; 3,248 vs. 3,780) when determined by Cytation5 workflow than when determined by Nikon workflow. Regardless, Pearson correlation of mean muscle fiber cross-sectional areas determined by Nikon and Cytation5 workflows was 0.73 (P < 0.01). In both workflows cross-sectional area of MyHC type I fibers was the smallest and area of MyHC type IIX fibers was the largest. These results validated the Cytation5 workflow as an efficient and biologically relevant tool to expedite data capture of muscle fiber characteristics while using objective thresholds for muscle fiber classification.