An inexpensive and simple approach using ultraviolet-spectroscopy to distinguish vinegar samples was developed. Vinegar samples were diluted with distilled water(water/vinegar was 6/1, v/v), then distilled with rotary evaporator at 45°C. The distilled liquid was introduced into the UV-Vis 2550 spectrophotometer to scan the UV spectrum from 245 nm to 330 nm, distilled water was used as reference solution. Once spectra were collected, principal components analysis (PCA) and artificial neural network (ANN) were employed for the exploratory analysis and the development of classification models, respectively. The criteria for discrimination were various raw materials and the different fermentation process of vinegars. The correct rate of the classification according to the production process was more than 90% and it was 100% according to the raw materials. The ANN model also could be used to class vinegar samples according to the raw materials, the correct rate was 80.95% in this research.