The present invention provides a computer implemented method for predicting the risk of posttransplant lymphoproliferative disorder as well as a computer implemented method for simultaneous predicting the risk of posttransplant lymphoproliferative disorder and differentiation of
Epstein Barr Virus (EBV)-positive from EBV-negative patients in posttransplant lymphoproliferative disorder and associated systems. The method for predicting the risk of posttransplant lymphoproliferative disorder PTLD, comprises the following steps: receiving information representative for expression level of biomarkers, acquired from a sample to be assessed, said biomarkers being at least three selected from the group comprising HSPA6, CD300A, IFITM1, SHFL, HMGB1, TMEM163, ELL3, GRHPR, GMDS, GALNT10, IRF1-AS1, IFIT5, MLLT3, KIR2DL4, CD1C, SP3, SLC6A16, COP1, classifying said information representative for expression level of said at least three biomarkers, outputting the classification results, said results being indicative of whether the assessed sample belongs to one of two classes: PTLD or non-PTLD patient. The present invention provides further biomarkers for predicting, diagnosing and differentiating of posttransplant
lymphoproliferative disorders and use thereof.