As calculated using health gap summary measures, suicide is predicted to rank as the fourteenth most burdensome global health condition by the year 2020, and suicide rates are still climbing rapidly in many countries of the world. Unfortunately, the unique and challenging methodological issues which confront clinical suicide epidemiologists complicate investigations which could potentially inform suicide prevention efforts. There is, for instance, a popular, albeit largely unexplored, theory that environmental and biological influences impact suicidal behavior differentially by age group. However, neither the validity of the theory itself nor the potential mediators of the age-suicide relationship are well explicated. The usual approach to age group analysis for suicide decedents is to use fixed intervals (e.g., five-year intervals) to define age groups. However, when the data are available for many years, the suicide rate can vary over time for a given age group, and displaying the rate over time for multiple age groups can be confusing. In this paper, we use a method of cluster analysis to derive internally consistent age groups which exhibit distinct changing patterns across time. The method is applied to the US suicide data between 1960 and 2007.