This paper investigates the effect of fiber-reinforced composites (FRPs) on the mechanical properties of concrete under ambient conditions. It begins with an examination of the various types of FRP and their advantages, followed by a review of isostructural models for passively restrained concrete under ambient conditions. These models are categorized into two main groups: those assuming constant confining stresses and those that incorporate stress constraints related to the loading history. Recent studies have highlighted the significant role of stress paths in determining the stress-strain behavior of concrete. Traditional methods for predicting the FRP-constrained concrete reinforcement bond at room temperature are increasingly being replaced by machine learning techniques, such as Artificial Neural Networks (ANNs) and Genetic Expression Programming (GEP), which offer superior accuracy in predicting the FRP-constrained concrete bond strength and the compressive properties of FRP-confined concrete columns. In particular, experimental results show that the compressive strength of FRP-confined concrete columns can increase by up to 30-250%. This review offers valuable insights into the effects of FRP on concrete and contributes to the advancement of engineering design practices.