Since the introduction of the fuel injection technology, engines have been more reliant on electronic components to perform highly sophisticated control strategies such as computing the optimal spark timing. Most of today’s vehicles rely on pre-computed values of spark timing for each operation condition which are then mapped into memory. This traditional look-up table approach does not scale well with changes in operating conditions and parameters, as the amount of required memory can grow very quickly. In this work, we present a crank-angle-resolved engine cylinder pressure estimation model that computes an estimation of the engine pressure based on specific conditions such as speed, amount of fuel being used, engine parameters, etc. This model is then used to generate meaningful parameters such as instant torque, optimal spark timing, etc. We validated our model using actual engine data. We tested 3 simple textbook sets as well as 10 sets provided by Fiat Chrysler®. We compared the estimated pressure against the real measured pressure trace. The average relative error is about 3% while the maximum relative error is 5%. The nature of the model requires a dedicated hardware implementation if it is to meet real-time operating conditions. The goal is to design an optimal hardware component for cylinder pressure estimation to be included in an embedded system for hardware-in-the-loop simulation.