In microarray experiments, the missing value does exist and somewhat affects the stability and precision of the expression data analysis. Compared with increasing experiments, missing value estimating is preferred in reducing the influence of missing values on the post-processing. With the kernel weight based on similarly between target gene and sample genes, which localize missing value estimation, a new method based on weighted regression is presented. On the two real microarray expression datasets, the novel method was compared with several existing methods. Experimental results show that the novel method has better stability and precision than the existing methods that have been employed.