Transfer functions and the number of neurons in each hidden layer were optimized to obtain the best structure of the proposed model. The best-reported topology includes seven to eight neurons with TANSIG-LOGSIG-purelin transfer functions. [PERSON] et al. [13] developed an ANN model to predict some of the kinetic parameters of the thermal decomposition of the mixture of polycarbonate and CaCO\({}_{3}\) using TGA experimental data. Three input parameters (temperature, conversion, and time) were used. Two statistical parameters, namely mean squared error and regression coefficient, were used to identify the best architecture of the proposed ANN model. [PERSON] et al. [14] investigated the thermodynamic and kinetic characteristics of the combustion of some blends at different CO\({}_{2}\)/O\({}_{2}\) ratios. In addition, an ANN model, with three input parameters (heating rate, temperature, and CO\({}_{2}\)/O\({}_{2}\) ratio), was developed to predict the mass loss percent using TGA data. In 2018, [PERSON] et al. [15] developed an ANN model using TGA data to predict the thermal decomposition of a sewage sludge that has a high ash contact. Good performance of the proposed ANN model was reported. [PERSON] et al. [16] studied the effect of microalgae ash catalysts on the pyrolysis of a mixture of a peanut shell and pure microalgae at different heating rates (10-100 K/min). Like the rest of the previous researchers, an ANN model, with heating rate and temperature as input variables, was developed to predict the weight loss percent of the mixture during its thermal decomposition using TGA data. [PERSON] and [PERSON] [17,18] and [PERSON] and [PERSON] [19] performed comprehensive investigations aiming to obtain the kinetic parameters of the pyrolysis of LDPE, catalytic pyrolysis of HDPE, and the co-pyrolysis of different polymer mixtures including PS, PP, LDPE, and HDPE. In addition, ANN modeling was attempted to predict the weight loss percent using TGA experimental data [17,18]. Excellent agreement between the experimental and predicted results was reported. [PERSON] et al. (2019) investigated the combustion of pet coke under an oxygen atmosphere at three different heating rates (10, 50, and 75 K/min) from 308 to 1173 K. An ANN model with LM algorithm was developed to predict the mass loss percent as a function of temperature and heating rate. A single-layer perception model (SLP) 2-6-1 and a multi-layer perception model between 2-14-6-1 and 2-14-7-6-1, with 11 different models, were tested. Three statistical parameters, namely coefficient of variation (R\({}^{2}\)), sum of deviation square (SS), and mean residual (MR), were used to evaluate the proposed models. The best architecture model was reported as NN7-MLP, 2-14-7-6-1. [PERSON] et al. (2018) investigated the catalytic co-pyrolysis of corn cob and high-density polyethylene (HDPE) at a wide range of heating rates (10-200 K/min) and temperatures (323-1173 K). One of the main objectives of that work was to develop an ANN model to predict the co-pyrolysis behavior and determine the thermogravimetric curves as a function of temperature, heating rate, and mixing ratio. Although extensive work has been performed to develop ANN models to predict the thermal decomposition data of pure polymers/materials, there is insufficient work targeting mixed plastic wastes. Therefore, this work aims to develop an efficient ANN model to predict the pyrolysis data of mixtures of four different polymers (PS, PP, LDPE, and HDPE) using experimental data published earlier ([PERSON] et al., 2018). In addition, sensitivity analysis using Pearson correlation was performed.