Polyethylenes (high density polyethylene (HDPE) and ultra-high molecular weight polyethylene (UHMWPE)) were extruded in a corotating twin-screw extruder under high temperatures – (320 °C < T < 420 °C) for various process conditions (flow rate and screw rotation speed). From the in line measurement of the die pressure, a numerical method based on the Carreau-Yasuda model was developed to predict the rheological behaviour (variation of the viscosity versus shear rate). The results were successfully compared to the viscosity measured from off-line measurement assuming the Cox-Merz law. Finally, Machine learning techniques, able to operate in the low-data limit, were tested to build predicting models of the process outputs and material characteristics.