A new copula model has been developed to better understand how two variables are related. This model can handle different types of relationships between the variables and provides more detailed information about their connection. By using a mixture of normal distributions, the copula captures a wide range of dependence patterns. The model was compared to other existing models and was found to be more flexible. It was tested on real data from astrophysics and agriculture, showing its ability to capture unique and asymmetric relationships between variables.