The cultural and creative industries have garnered widespread attention as an important vehicle for promoting the transformation and upgrading of urban industrial structures. In this investigation, we take Harbin—a city in China with a strong industrial legacy—as a case study. Through kernel density analysis and the DBSCAN clustering algorithm, we identify and analyze the spatial distribution and spatiotemporal evolution patterns of 157 clusters of cultural and creative industries in Harbin. We construct a Geographic Weighted Regression (GWR) model using 20 indicators from three categories (i.e., social, cultural, and economic) to analyze the factors impacting the agglomeration of cultural and creative industries in Harbin. Our findings reveal that the cultural and creative industries exhibit an agglomeration pattern. A large-scale agglomeration area for large enterprises has formed in the city center, while scattered, small-scale agglomeration zones for emerging small enterprises have formed in newly developed areas on the urban periphery. The GWR analysis indicates that economic factors have the most significant impact on the agglomeration of cultural and creative industries; however, night-time economic facilities show a negative correlation. Among social factors, the convenience of public transportation and new energy transportation infrastructure have a significant impact on industrial agglomeration. Regarding cultural factors, cultural and sports facilities have the greatest influence, while public information kiosks and public arts education facilities exhibit spatial variability. These findings provide a scientific basis for policy formulation and contribute to promoting the healthy development of cultural and creative industries.