Abstract Neural networks with pruning were applied to model overlapped peaks obtained in differential pulse voltammetry (DPV) with modified carbon fibre electrode with TiO 2 of binary mixtures of catechol and hydroquinone. The best condition for electrochemical response was obtained with 0.05 mol l −1 Tris–HCl buffer at pH 6.0 and T-800 sized carbon fibre electrode. Initially the voltammograms were processed using Fourier transform filter and principal component analysis (PCA) to noise reduction and data compression, respectively. The scores of these principal components were the input into the neural network and the optimal brain surgeon (OBS) was the procedure employed for pruning the neural network. The results obtained with pruning procedure were slightly better in relation to hydroquinone in comparison to the PLS1 and PLS2. However, the similar errors were obtained to catechol when using PLS or neural networks models. Using neural networks with pruning was possible to determine catechol and hydroquinone by DPV using carbon fibre electrode, in concentration range of 1.0×10 −4 up to 6.0×10 −4 mol l −1 with root mean square errors of predictions (%RMSEP) of 7.42 and 8.02, respectively. The good results show that the proposed methodology is a good alternative to simultaneous determination of catechol and hydroquinone in binary mixtures.