This work presents the short-term creep behavior of novel epoxy composites reinforced by post-consumed yerba-mate (YM). Particulate composites were manufactured using 5, 10, and 20 wt.% of YM. The composite morphologies were related to the dynamic mechanical and creep behavior at the glassy state (∼30°C). Creep tests were performed using three different stress loads (1.5, 3.0, and 6.0 MPa). Weibull model, Artificial Neural Network (ANN) approach and Response Surface Methodology (RSM) were used to fit the experimental curves and to predict results. A better fit was obtained using the ANN approach than the Weibull model due to the capability of ANN to learn from own data and in fitting complex nonlinear data. The RSM approach proved to be an intelligent and reliable technique to access a higher range of results, reducing experimental time and cost and keeping statistical significance. Also, the present methodology can be extended to model and predict other properties and/or optimize parameters.