Knowing the charge state of an ion in a mass spectrum is crucial to being able to assign a formula to it. For many small-molecule peaks in complex mass spectra, the intensities of the isotopic peaks are too low to allow the charge state to be calculated from isotopic spacings, which is the basis of the conventional method of determining the charge state of an ion. A novel artificial intelligence derived method for identifying the charge state of ions, in the absence of any isotopic information or a series of charge states, has been developed using an artificial immune system approach. This technique has been tested against synthetic and real data sets and has proven successful in identifying the majority of multiply charged ions, thereby significantly improving the peak assignment rate and confidence.