This paper presents the development of a soft-sensor receiving as inputs Pressure Stimulated Current (PSC) characteristics in order to predict a critical mechanical property of cement-based materials, in a non-destructive manner. The soft-sensor is based on a Radial Basis Function (RBF) network that starts with an empty hidden layer and evolves its structure and synaptic weights as new data become available. Results have shown that the proposed approach can be used successfully to evolve a predictive tool based on input-output data, whereas it is superior compared to other adaptive modeling techniques.