Lignocellulosic biomasses have emerged as one of the cheap and sustainable raw materials for the production of platform chemicals and fuels through various biorefinery processes. Depending on the biorefinery processing techniques, the conversion processes are influenced by various parameters like temperature, concentration of acid or enzymes, time, solid-to-liquid ratio and composition of the feedstocks, among others, which in turn influences the final output in terms of yield and quality. Mathematical modelling using response surface methodology and artificial intelligence techniques like artificial neural network (ANN), fuzzy inference system (FIS) and genetic algorithm (GA) are very promising predictive modelling tools for determining the interaction between the parameters, involved in the conversion processes, for the purpose of optimisation of reaction conditions to obtain desired yield and purity of the output. These techniques reduce the need for time and resource consuming experimentation and have shown outstanding accuracy in predicting the optimal reactions conditions by analysing the non-linear interactions between the different parameters. In the recent years, these artificial intelligence-based modelling tools have revolutionised the process designing of biorefinery techniques by improving the process intensification, which has significant impact on process economies. The artificial neural network and fuzzy inference system techniques provide an excellent advantage in pattern recognition when interpreting the influence of various parameters involved in complex biorefinery processes compared to the traditional mathematical modelling using response surface methodology. These artificial intelligence-based techniques are going to be an integral part of biorefinery process designing in the future years to come as computational techniques continue to grow. Therefore, this chapter deals with the various studies that have been attempted to use the power of ANN, FIS, GA and other emerging computational techniques in biorefinery process designing for circular bioeconomy.