Indirect predictions (IP) can be obtained for young animals that are not yet included or will never make up to an official genomic evaluation. Additionally, if lots of animals are genotyped but they do not contribute to the evaluation, having IP for them would reduce computing cost. This is beneficial if accuracy levels are maintained. If single-step GBLUP (ssGBLUP) is the official evaluation method, SNP effects can be obtained by backsolving genomic EBV (GEBV). Subsequently, IP are obtained by the sum of SNP effects weighted by gene content. When IP are released, a measure of accuracy that reflects the standard error of IP is needed. Our objective was to implement formulas to calculate accuracy for IP and to apply the method in a cattle population. The American Angus data used in this study consisted of 35k records for post-weaning gain and pedigree information for 202k animals, of which 60k were genotyped for 38.4k SNP (after quality control). From the genotyped animals, 2k were in the validation set. A complete dataset had phenotypes and pedigree up to 2013, genotypes up to 2014, and was used to calculate the benchmark accuracy by the inverse of the LHS. This accuracy is referred to as GEBV accuracy. A reduced dataset had phenotypes, pedigree and genotypes up to 2013, and was used to obtain the prediction error covariance (PEC) for SNP effects. This PEC was used to calculate IP accuracy. The process of obtaining IP accuracy involved several steps: factorization and inversion of the LHS of ssGBLUP mixed model equations; extraction of the inverse of the LHS for genotyped animals; calculation of SNP effects from GEBV; computation of PEC for SNP effects; calculation of IP; computation of accuracy of IP as a function of PEC for SNP effect and SNP content. Correlations between GEBV and IP accuracies were over 0.997, indicating the possibility of getting a good measure of IP accuracy based on ssGBLUP, without directly switching to a SNP-BLUP model. Obtaining IP accuracies from large-scale ssGBLUP evaluations, which use the algorithm for proven and young, will be the subject of future investigations.