Glycans attached to proteins play a significant role in the interaction with other molecules. They also participate in processes like protein folding and secretion. Furtermore, glycans affect protein function, stability and half-life. The most important property of glycoproteins is their microheterogeneity because different glycans can bind to the same glycosilation site on a specific protein resulting in various glycoforms of the protein. Most research has been conducted on N-glycans and changes in N-glycoma of biological samples, such as blood plasma or individual proteins like IgGs. Changes in N-glycosylation have been observed in various physiological conditions such as adolescence and pregnancy, but also in many diseases. Therefore, an increase in research has been observed for the purpose of detecting biomarkers for various diseases, early diagnosis or prognosis of outcomes and, ultimately, the development of personalized medicine. High-troughput metods are used to manage and analyze a large number of samples in a short period of time. HILIC-UPLC and xCGE-LIF are two such high-throughput methods used to analyze N-glycans. In this paper the repeatability and reproducibility of these two methods are oberved on three different standard samples. It is important to determine the repeatability and reproducibility of the methods to ensure that the observed differences between the analyzed samples are indeed a consequence of the difference between the samples and not a reflection of the method error. Each step of the method has a variation that contibutes to the final CV value. After analyzing the obtained data and comparing calculated coefficients of variation (CV values), it was determined that both methods are reliable for study of both plasma protein and IgG N-glycans. HILIC-UPLC method in comparison to xCGE-LIF, shows better repeatability and reproducibility. On the other hand, xCGE-LIF method can analyse larger number of samples in given time. Moreover, xCGE-LIF shows better separation of the peaks, method is more sensitive and can analyse smaller sample quantities. It is usefull to know the advantages and disadvantages of each method in order to select the optimal one for each research. Optimisation of sample preparation can reduce CV values for each peak and influence repeatability and reproducibility of the method. To diminish the impact of a measurement error on obtained results, a good study design, sample randomisation, and following of standard operating procedures are of great importance. Further research is needed to identify the steps that bring the most variation to the methods and to explore ways to better and improve the methods for N-glycan analysis.