Pathogenic splicing alterations caused by point mutations in both splice sites and auxiliary cis-regulatory elements are increasingly recognized as an important mechanism through which gene mutations cause human disease. Unfortunately, in routine genetic diagnostic settings, splicing mutations may escape identification, due to the lack of RNA samples. Since most patients are genotyped only, any computational prediction of mutation effects on splicing can be beneficial for the human geneticist. Here, we review common techniques to identify human point mutations and delineate the molecular basis for splice site recognition. Moreover, this article provides basic insights into web-tools predicting splice sites and cis-regulatory elements and discusses their benefits for judgment of clinically identified sequence variants of disease-specific genes.