Turbocharging has become the favoured approach for downsizing internal combustion engines to reduce fuel consumption and CO2 emissions, without sacrificing performance. Matching a turbocharger to an engine requires a careful balance of various design variables in order to meet the desired performance. Once an initial selection of potential compressor and turbine options is made, corresponding performance maps are evaluated in engine cycle simulations to down-select the best combination. This is the conventional matching procedure used in industry. It’s “passive” in that it relies on measured maps, thus only existing designs may be evaluated. In other words, turbine characteristics cannot be changed during matching so as to explore the effect of slight design adjustments. Instead, this paper presents an “adaptive” matching methodology for the turbocharger turbine. By coupling an engine cycle simulation to a turbine meanline model (“in-the-loop”), adjustments in turbine geometry are reflected in both the exhaust boundary conditions and overall engine performance. By running the coupled engine-turbine model within an optimization framework, the optimal turbine design will evolve. The methodology is applied to a 1.2L turbocharged gasoline passenger car engine, with the objective of minimizing fuel consumption over a representative drive cycle while meeting performance constraints. The turbine design is optimized over a number of steady-state operating points, using the production geometry as the baseline. Despite the current series production turbine being a very good match already, and with optimization restricted to a handful of parameters, simulation results suggest there remains a small but useful margin for system efficiency gains. The proposed methodology is not only useful for directing improvements of existing designs; it can also be used to develop a bespoke turbine geometry in new engine projects where there is no previously available match. For these reasons, in time, adaptive turbo matching will become the standard approach.