Habitat suitability refers to the assessment of environmental conditions favoring the growth and survival of a particular species. In recent times, understanding habitat suitability has become crucial for conservation efforts, ecological management, and predicting species distributions in the face of environmental changes. This study focuses on the habitat suitability of Glycyrrhiza glabra in the Hatay region. Variations in temperature, precipitation patterns, and land use have changed the geographical distribution of plant species, making it more difficult for them to grow and regenerate in the area. In response to these environmental changes, our study utilizes spatial modeling techniques to evaluate and forecast habitat suitability for these plant species in diverse locations. By understanding these dynamics, we aim to identify suitable environments for future agricultural production and implement techniques for preserving resources that are efficient and suited to the unique environmental conditions of the Hatay region. Leveraging 355 presence points and incorporating 53 conditioning factors, our spatial modeling utilized Support Vector Machine (SVM), Maximum Entropy (MaxEnt), and Random Forest models. The achieved accuracies were commendable, with SVM boasting an accuracy of 81% and MaxEnt at 98%. Random forest yielded 91% accuracy. In our analysis, we used the Variance Inflation Factor (VIF) and examined coefficients to determine which environmental factors to eliminate from further consideration in our study. This unique approach of considering an extensive set of environmental factors sets our work apart, offering a more comprehensive understanding of habitat suitability.