Titanium dioxide has been widely applied by industry and scientific research as a photocatalyst,whose main drawback still has been the application under visible light.Properties such as phases amount,crystallite size, specific surface area, pore volume, and band gap value (Eg)have been explored by synthesis methods to improve TiO2 s performance. However, they are empirically adjusted.The present work was carried out to describe an analytical relation between those properties for photocatalysis, using Artificial Neural Networks (ANNs) as a statistical tool. Aiming the most representative set, 53 literature papers were used for the database. Eg was considered the measurement which evaluates the photocatalytic performance, namely the network s out put variable. Two blocks A and B, which are distinguished by input variables, were arranged into groups to investigate the variables pair influences, using 257 and 220 photocatalysts vectors for each,respectively. Modelling attempts examined different training algorithms(based on Back- propagation), types of networks (Feedforward, Cascade forward and Elman), transfer functions, number of hidden neurons, and multilayer network.The developedmodelswereevaluatedbythesumofsquarederror(SSE),the correlation coefficient(R2) of regression for both training and test data, the prediction behaviour of the dataset,and the regression diagram of predicted and observed values. The block A results suggest the variables do not have an apparent relationship. Multilayers models on block B revealed an increase of network identification performance. The result with the highest coefficient showed 4-4-6-1 topology; corresponding, respectively, to input, first hidden, second hidden and output layers.It had R2 of 84 percent for training and to 50 percent fortest, with SSE of 2.24.This result suggests this network is not able topredict the Eg, but it can be improved. The structural properties should be reviewed, according to standards of characterization and statistical data. Hence, the model could be well fitted, optimized, and used for photocatalysis improvement.