This study investigates the internal structure of climate change awareness within Egyptian society. It uses neural network analysis to explore its relationships with demographic factors such as gender, academic level, residence, and age. Data were collected from 433 participants through social media platforms like WhatsApp and Facebook, offering a diverse population representation. Advanced statistical analysis, including neural network analysis, t-tests, ANOVA, and Pearson's correlation, was applied to comprehensively understand the results. The neural network revealed 14 interconnected nodes, encompassing climate change awareness items and demographic variables, organized into three distinct clusters. Key mediators identified in the network included gender, belief in deforestation as a significant cause, and the recognition of climate change as a real phenomenon. The study highlighted the strongest relationships centered on the global need for coordinated action to address climate change. While no significant differences were found across gender, academic level, or residence, a positive correlation between age and climate change awareness was identified, with older participants showing a more profound understanding of the issue. The findings suggest that tailored interventions for younger demographics and incorporating climate change education into academic curricula are crucial for nurturing environmental awareness. The study also emphasizes the importance of inclusive strategies and diverse sampling methods in future research to broaden climate change awareness across Egyptian society, thereby fostering more effective engagement with the topic.