This chapter introduces the Partial Least Squares (PLS) approach for evaluating structural equation models (SEM). The authors aim to provide a comprehensive guide for assessing PLS models, which are advantageous for testing theories due to their fewer requirements compared to covariance structure analyses and their ability to handle both reflective and formative indicators within the same model. However, there is a lack of established criteria for evaluating PLS models, especially for formative constructs. The chapter highlights the growing interest in SEM and the challenges associated with traditional methods like covariance structure analysis, particularly in handling formative measurement models. It emphasizes the need for appropriate evaluation criteria and presents a detailed guideline for assessing both reflective and formative measurement models, supported by an empirical example of repeat purchasing behavior.This chapter introduces the Partial Least Squares (PLS) approach for evaluating structural equation models (SEM). The authors aim to provide a comprehensive guide for assessing PLS models, which are advantageous for testing theories due to their fewer requirements compared to covariance structure analyses and their ability to handle both reflective and formative indicators within the same model. However, there is a lack of established criteria for evaluating PLS models, especially for formative constructs. The chapter highlights the growing interest in SEM and the challenges associated with traditional methods like covariance structure analysis, particularly in handling formative measurement models. It emphasizes the need for appropriate evaluation criteria and presents a detailed guideline for assessing both reflective and formative measurement models, supported by an empirical example of repeat purchasing behavior.