There have been many linear regression models proposed to analyze mixture experiments, such as Scheffé model, Slack-Variable model, and Kronecker model. Among these models, the Slack-Variable model is the most controversial one. On one hand, it is very popular among practitioners, especially formulators. On the other hand, it is not so favored by academic statisticians. In this Research Protocol, we advocate that for some mixture experiments the Slack-Variable model has some appealing properties including numerical stability and better prediction accuracy when variable selection is performed.  We also discuss how to choose the component as the slack variable, what transformation should be used to reduce the collinearity, and under what circumstances the Slack-Variable model should be used and can be more stable than other types of models.