Nowadays, the development of a new engine is becoming more and more complex due to conflicting factors regarding technical, environmental and economic issues. The experimental activity has to comply with the above complexities, resulting in increasing cost and duration of engine development. For this reason, the simulation is becoming even more prominent, thanks to its lower financial burden, together with the need of an improved predictive capability. Among the other numerical approaches, the 1D models represent a proper compromise between reliability and computational effort, especially if the engine behavior has to be investigated over a number of operating conditions. The combustion model has a key role in this contest and the research of consistent approaches is still on going.In this paper, two well-assessed combustion models for Spark Ignition (SI) engines are described and compared: the eddy burn-up theory and the fractal approach. Both are embedded in the commercial software GT-Power™ under the form of “user routine”.The main aim of the paper is a detailed appraisal of the above combustion models, carried out with reference to three different SI engines, fueled with commercial gasolines, both at full and part load operation. In a first stage, the background theory of both models is presented and an extension of the fractal model is also proposed. A sensitivity analysis is performed to investigate the effects of tuning constants included in each model. Then, they are tuned with reference to experimental data at full load and a single set of constants is established for each engine. Tunability efforts are also discussed.The predictive capabilities of the combustion models are compared and discussed under various operating conditions, in terms of characteristic combustion events and burn rate profiles. Finally, in order to also assess the physical strength of both models, a fourth engine is investigated in a “blind” test, without performing a dedicated tuning. The results showed that the fractal and eddy burn-up combustion models exhibit similar accuracy levels, and guarantee satisfactory reliability and applicability to various engines and operating conditions. However, the fractal approach denoted an easier tunability and a slight higher predictivity.