The olive oil industry is an important source of agricultural residues throughout its value chain, ranging from intermediate process slurries to relatively dry content pruning residues. Among them, crude olive pomace (COP) is of particular interest since it is abundant, low cost and can be a promising source for bioenergy. Nevertheless, because COP is phytotoxic and has a high moisture content and low energy density, it represents a challenge to conventional processes that usually require a dry and homogenous material. The main novelty of this study is the use of a transition metal catalyst and a central composite design (CCD) approach to optimize the conversion of COP through hydrothermal liquefaction (HTL) into valuable products. Results show that catalytic HTL is capable of converting up to half of the COP into bio-oil. Higher process temperatures resulted in lower bio-oil yields but larger higher heating value (HHV) and lower N content. The bio-oils produced at higher temperatures also show lower concentration of phenols and regarding biochar, a low inorganic content. Without any further upgrading, COP bio-oils produced by HTL are rich in valuable compounds such as oleic acid, phenolic compounds and ketones that can be used in the polymer industry or as chemical intermediates. The highest bio-oil yield was 51.96 wt% at 330 ºC for 30 min and 7.5 wt% catalyst with a HHV of 22.0 MJ/kg. At those operational conditions, the biochar yield was 16.49 wt% with a HHV of 8.9 MJ/kg. The major minerals found in the biochars (CaO, SiO₂ and P₂O₅) suggests that biochar could be well-suited for use in soil applications or as materials for adsorption, especially the non-catalytic ones. Furthermore, the experimental results acquired from HTL of COP were used to develop a global kinetic model. Using an explicit Runge-Kutta method, the kinetic parameters were calculated. After comparing the global kinetic model with a linear system of ordinary differential equations (ODEs) based on the CCD models, results indicate that this approach is more effective in predicting the yields of HTL products.