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Affymetrix human gene expression microarrays are widely used in gene expression analysis. However, the comparability of data analyzed in different laboratories is not self-evident hindering integration of multiple data sets. In this study, we introduce a novel normalization method, Weibull distribution based normalization that makes the data from different laboratories easier to integrate and compare. The method normalizes the samples by correcting the ML-estimates of the parameters of Weibull distribution to be the same in every sample of the same array generation. The effects of the Weibull distribution based normalization were studied by comparing the distributions of the samples, examining the deviations of expression levels of housekeeping genes, and clustering the data.