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Icelandic Cattle is a local dairy cattle breed in Iceland. With about 26,000 breeding females, it is by far the largest among the indigenous Nordic cattle breeds. The objective of this study was to investigate the feasibility of genomic selection in Icelandic Cattle. Pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) were compared. Accuracy, bias, and dispersion of estimated breeding values (EBV) for milk yield (MY), fat yield (FY), protein yield (PY), and somatic cell score (SCS) were estimated in a cross validation-based design. Accuracy (⁠ r ^ ⁠) was estimated by the correlation between EBV and corrected phenotype in a validation set. The accuracy (⁠ r ^ ⁠) of predictions using ssGBLUP increased by 13, 23, 19, and 20 percentage points for MY, FY, PY, and SCS for genotyped animals, compared with PBLUP. The accuracy of nongenotyped animals was not improved for MY and PY, but increased by 0.9 and 3.5 percentage points for FY and SCS. We used the linear regression (LR) method to quantify relative improvements in accuracy, bias (⁠ Δ ^ ⁠), and dispersion (⁠ b ^ ⁠) of EBV. Using the LR method, the relative improvements in accuracy of validation from PBLUP to ssGBLUP were 43%, 60%, 50%, and 48% for genotyped animals for MY, FY, PY, and SCS. Single-step GBLUP EBV were less underestimated (⁠ Δ ^ ⁠), and less overdispersed (⁠ b ^ ⁠) than PBLUP EBV for FY and PY. Pedigree-based BLUP EBV were close to unbiased for MY and SCS. Single-step GBLUP underestimated MY EBV but overestimated SCS EBV. Based on the average accuracy of 0.45 for ssGBLUP EBV obtained in this study, selection intensities according to the breeding scheme of Icelandic Cattle, and assuming a generation interval of 2.0 yr for sires of bulls, sires of dams and dams of bulls, genetic gain in Icelandic Cattle could be increased by about 50% relative to the current breeding scheme. [ABSTRACT FROM AUTHOR]