Aggregates of amyloid-beta (Aβ) peptides are thought to be involved in the development of Alzheimer's disease because they can change synaptic plasticity and induce neuronal cell death by inflammation, oxidative damage, and transmembrane pore formation. Exactly which oligomeric species underlie these cytotoxic effects remains unclear. The work presented here established well-controlled aggregation conditions of Aβ₁₋₄₀ or Aβ₁₋₄₂ peptides over a 20-day period and characterized these preparations with regard to their β-sheet content, degree of fibril formation, relative abundance of various oligomer sizes, and propensity to induce membrane pore formation and cytotoxicity. Using this multivariate data set, a systematic and inherently unbiased partial least squares (PLS) approach showed that for both peptides the abundance of oligomers in the tetramer to 13-mer range contributed positively to both pore formation and cytotoxicity, while monomers, dimers, trimers, and the largest oligomers (>210 kDa) were negatively correlated to both phenomena. Multivariate PLS analysis is ideally suited to handle complex data sets and interdependent variables such as relative oligomer concentrations, making it possible to elucidate structure function relationships in complex mixtures. This approach, therefore, introduces an enabling tool to the field of amyloid research, in which it is often difficult to interpret the activity of individual species within a complex mixture of bioactive species.