Labelling of therapeutic antibodies with radionuclides or fluorophores is routinely used to study their pharmacokinetic properties. A critical assumption in utilizing labelled therapeutic antibodies is that the label has no unfavourable effects on antibody charge, hydrophobicity, or receptor affinity. Ideally, the labelled protein should not have any significant deviations from the physiological properties of the original molecule. This article describes an established quality in vitro assessment workflow for labelled antibodies that ensures better prediction of changes in antibody pharmacokinetic (PK) properties after modifications. This analysis package considers degradation and aggregation analysis by size-exclusion chromatography, changes in neonatal-Fc-receptor (FcRn) affinity, and heparin interaction. FcRn binding is important for antibody recycling and half-life extension, whereas heparin affinity provides estimates on the rate of endocytosis through unspecific cell surface binding. Additionally, mass spectrometric analysis to determine the degree of labelling (DoL) completes the package and the combined analysis data allow to predict the label contribution to the PK properties of the modified antibody. This analytical strategy for labelling 11 IgGs has been investigated using 2 different IgG1 constructs and applying 7 different types of labels. Each labelling resulted in a change in the physicochemical properties of the protein. Not only can the DoL of modified IgGs lead to a change in protein properties, but the type of label also can. Furthermore, it was demonstrated that the labelling process can also influence the behaviour of labelled mAbs. An identical label on different constructs of IgG1 can cause different affinities for FcRn and heparin. Considering the assessment data, only 6 of the 11 modified antibodies from this study can be recommended for subsequent experiments. In conclusion, a suitability assessment of labelled antibodies prior to any pharmacokinetic studies is essential to reduce cost, allocate resources and reduce the number of animal experiments during pre-clinical drug development.