More and more stringent emission regulations and the desire to reduce fuel consumption lead to an increasing demand for precise and close-loop combustion control of diesel engines. Cylinder pressure-based combustion control is gradually used for diesel engines in order to enhance emission robustness and reduce fuel consumption. However, it increases the cost. In this paper, a new prediction method of combustion parameters including cylinder pressure is presented for diesel engines. The experiment was carried out on a engine test bench to obtain the ECU (Electronic Control Unit) signals of a heavy-duty diesel engine by calibration software. The combustion parameters is measured by a combustion analyzer, such cylinder pressure, combustion center of gravity (CA50) and the maximum combustion temperature (MCT). A combustion model using genetic programming (GP) is built. The input parameters are chosen from the ECU signals, such as engine speed, engine load, injection quantities, inlet air flow. The output parameters are cylinder pressure, CA50 and MCT. The combustion model is trained and validated by measurement data. The results indicate that the cylinder pressure model can be built with the input parameters of engine speed, injection quantities, inlet air flow and exhaust air temperature. The correlation coefficient between simulation and experiment data is 0.938 and the average relative error is 4.0%.