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Understanding memory in the context of data visualizations is paramount for effective design. While immediate clarity in a visualization is crucial, retention of its information determines its long‐term impact. While extensive research has underscored the elements enhancing visualization memorability, a limited body of work has delved into modeling the recall process. This study investigates the temporal dynamics of visualization recall, focusing on factors influencing recollection, shifts in recall veracity, and the role of participant demographics. Using data from an empirical study (n = 104), we propose a novel approach combining temporal clustering and handcrafted features to model recall over time. A long short‐term memory (LSTM) model with attention mechanisms predicts recall patterns, revealing alignment with informativeness scores and participant characteristics. Our findings show that perceived informativeness dictates recall focus, with more informative visualizations eliciting narrative‐driven insights and less informative ones prompting aesthetic‐driven responses. Recall accuracy diminishes over time, particularly for unfamiliar visualizations, with age and education significantly shaping recall emphases. These insights advance our understanding of visualization recall, offering practical guidance for designing visualizations that enhance retention and comprehension. All data and materials are available at: https://osf.io/ghe2j/'>https://osf.io/ghe2j/.