Thermodynamic calculations have the potential to provide new insight into old problems. They guide us to ideas about igneous process that are consistent with phase equilibria and are physically and chemically feasible. There are several points which relate to the modelling of magma mixing processes which bear restatement: (1) The important parameters governing differentiation by magma mixing contrast the parameters controlling conventional differentiation such as fractional crystallization. Whereas heat loss and decreasing temperature are the major variables driving conventional differentiation, magma mixing is driven by influxes of magma of different compositions and thermodynamic states. The fact that temperature can rarely be used as an independent variable in modelling magma mixing requires that other geologically sensible thermodynamic restrictions be found. (2) Thermodynamic modelling can refine our understanding of this important magmatic process because: (i) The calculations quantify the consequences of magma mixing. The computed parameters are easily compared against actual data and are a measure by which the magma mixing hypotheses can be judged; and (ii) Where the hypothesis is viable, modelling constrains the physical chemical behaviour of the system and gives us estimates of its effects on the surroundings (e.g., heat transfer rates etc.). (3) Whereas the thermodynamic simulation of magma mixing increases our current understanding, future studies must also include the physics of the process (e.g., Oldenburg et al., 1989), ensuring that our conceptions are physically reasonable as well as thermodynamically sound. There is, however, one final consideration which concerns modelling of magmatic processes: the strength and utility of a model resides in its ability to be tested against nature. Models producing only parameters that cannot be compared against observation and measurement are of little scientific use. Thermodynamic modelling of igneous processes is scientifically effective because it provides a plethora of parameters for testing against data.