Intracranial pressure (ICP) is a critical biomarker measured invasively with the risk of complications. There is a need for non-invasive methods to estimate ICP. Diffuse correlation spectroscopy (DCS) allows the non-invasive measurement of pulsatile, microvascular cerebral blood flow which contains information about ICP. Recently, our proof-of-concept study used machine-learning to deduce ICP from DCS signals to estimate ICP resulting in excellent linearity and a reasonable accuracy (±4 mmHg). Here, we extend to a multi-center (three centers) data set of adults with acute brain injury (N=34). We will present the results from the complete data set as new data flows in.