As the vehicle technology evolves and becomes more complex, the ability to monitor certain uncontrollable factors is possible through various engine management system calibration methods. Additionally, different optimization approaches assist in improving engine output characteristics. Advances in fuel production from unique feedstocks have paved a way for the introduction of innovative flex-fuel engines. These engines are made multi-fuel adaptive by utilizing appropriate calibration and optimization approaches. Since numerous researches have been carried out in internal combustion engine calibration, operating on alternative fuels, it is quite hard to maintain a record for this wealth of information. Therefore to bridge this issue, this study intends to organize and provide the reader with a retrospective view of selective studies undergone in the field of engine calibration using different tuning techniques. The objective of this study is to assist engine calibration enthusiasts on selecting an apt engine calibration technique for their application which can be flexible for multiple fuel types. Studies revealed that model-based calibration assisted by Gaussian process modelling and Design of Experiment application is adequate for calibrating an engine operating on alternative fuels. Additionally, calibration methodologies followed for certain fuel types and compositions are highlighted in detail. Furthermore, an advanced calibration methodology is proposed for flex-fuel engines in this study based on the knowledge gained through the preparation of this article. To further enhance accuracy, complex optimizers like neural networks can be used in the proposed methodology to initiate real-time calibration for ideal flex-fuel engine output responses. © 2020 Elsevier Ltd