Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case–control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1_rs2237892T allele or the CDKN2A-2B_rs2383208G/G, IGF1_rs35767T/T and MADD_rs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32–2.13) whereas those carrying the KCNJ11_rs5215C, KCNJ11_rs5219T and THADA_rs7578597C alleles or the FTO_rs8050136A/A and LTA_rs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76–0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10⁻⁰⁶). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30_rs2641348 and NOTCH2_rs10923931 variants (P_interaction=0.001 and 0.0004, respectively). Men carrying the ADAM30_rs2641348C and NOTCH2_rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (OR_M=0.71 and OR_M=0.66 vs OR_W=1.22 and OR_W=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.