A pattern-based recognition approach for the rapid determination of the identity, concentration, and enantiomeric excess of chiral vicinal diols, specifically threo diols, has been developed. A diverse enantioselective sensor array was generated using three chiral boronic acid receptors and three pH indicators. The optical response produced by the sensor array was analyzed by two pattern-recognition algorithms: principal component analysis and artificial neural networks. Principal component analysis demonstrated good chemoselective and enantioselective separation of the analytes, and an artificial neural network was used to accurately determine the concentrations and enantiomeric excesses of five unknown samples with an average absolute error of +/- 0.08 mM in concentration and 3.6% in enantiomeric excess. The speed of the analysis was enhanced by using a 96-well plate format, portending applications in high-throughput screening for asymmetric-catalyst discovery. X-ray crystallography and B-11 NMR spectroscopy was utilized to study the enantioselective nature of the boronic acid host 2.