Genome-wide association studies typically use genotyping arrays to genotype large sets of individuals and thus determine which SNPs are significantly overrepresented in the cases compared to the controls and thus determine association with disease. Genotyping arrays are cheaper than sequencing, but only measure selected SNPs across the genome. To increase the number of SNPs, genotype imputation is performed. Some regions within the human genome such as the Human Leukocyte Antigen (HLA) region, are highly variable and thus difficult to impute. The HLA region plays an important role in autoimmune and infectious diseases. In view of this, it is important to evaluate the accuracy of HLA imputation, especially in African populations as they have high diversity, and this has not been extensively studied. The aim of this study was to therefore evaluate the accuracy of HLA imputation in selected African populations. The study sets were selected from the Gambian individuals within the GGVP datasets. The Illumina Omni 2.5 array and H3Africa array data were inferred from the GGVP datasets using matching markers. The reference datasets were chosen from the 1kg-All, 1kg-Afr, 1kg-Gwd and H3Africa populations. HLA-A, HLA-B and HLA-C alleles were imputed using HIBAG and SNP2HLA while HLA SNPs were imputed using Minimac4, IMPUTE5 and SNP2HLA imputation tools. The assessment metrics were concordance rate and squared Pearson correlation coefficient. The most preferable software was HIBAG for HLA alleles imputation and IMPUTE5 for HLA SNPs imputation. The 1kg-All reference panel was the best performing reference panel for HLA alleles imputation implying that the reference panel sample size influences HLA alleles imputation. For HLA SNPs imputation, the 1kg-Gwd reference outperformed the other reference panels depicting that population specificity is key when imputing HLA SNPs. The H3Africa array and Illumina Omni 2.5 array performance were comparable for both HLA alleles and HLA SNPs imputation showing that genotyping arrays have less influence on HLA imputation in African populations. HLA SNPs with low minor allele frequencies (MAF) were imputed less accurately suggesting the need to build new algorithms and larger population-specific reference panels with an aim of improving imputation of HLA SNPs with low MAF.