The genus Actaea (including Cimicifuga) has been the source of ∼200 cycloartane triterpenes. While they are major bioactive constituents of complementary and alternative medicines, their structural similarity is a major dereplication problem. Moreover, their trivial names seldom indicate the actual structure. This project develops two new tools for Actaea triterpenes that enable rapid dereplication of more than 170 known triterpenes and facilitates elucidation of new compounds. A predictive computational model based on classification binary trees (CBTs) allows in silico determination of the aglycone type. This tool utilizes the Me (1)H NMR chemical shifts and has potential to be applicable to other natural products. Actaea triterpene dereplication is supported by a new systematic naming scheme. A combination of CBTs, (1)H NMR deconvolution, characteristic (1)H NMR signals, and quantitative (1)H NMR (qHNMR) led to the unambiguous identification of minor constituents in residually complex triterpene samples. Utilizing a 1.7 mm cryo-microprobe at 700 MHz, qHNMR enabled characterization of residual complexity at the 10-20 μg level in a 1-5 mg sample. The identification of five co-occurring minor constituents, belonging to four different triterpene skeleton types, in a repeatedly purified natural product emphasizes the critical need for the evaluation of residual complexity of reference materials, especially when used for biological assessment.