Under the "dual carbon" goals, urban parks, as important green infrastructure, play an increasingly prominent role in addressing climate change through their carbon sequestration functions. Research has shown that plants in green spaces can absorb a portion of carbon emissions in urban areas, achieving carbon neutrality when the carbon sequestration capacity of plants offsets the carbon emissions. However, the timing of when park green spaces can achieve carbon neutrality has been rarely studied, and existing research faces limitations in guiding engineering practices. Despite numerous scholars calculating annual carbon sequestration rates, the growth rate of trees is not linearly increasing, and current studies often overlook the massive embedded carbon emissions from park buildings despite their small footprint, leading to incomplete assessments. This study aims to develop a carbon neutrality timing prediction model based on the bill of quantities. To ensure the model's applicability across different climate zones, we collected engineering quantity lists and design drawings from 20 park projects in eastern and southern China, extracting seedling specifications, quantities, and building material data. We calculated the carbon sequestration increment of each tree within a specified period based on the diameter at breast height (DBH) - biomass allometric growth equation, and established a fitting equation with the increment of DBH (ΔDBH). The model utilizes the Chapman-Richards growth equation to simulate the non-linear growth process of trees, accounting for the fact that tree growth rates decrease with age rather than maintaining linear progression. Subsequently, by setting the carbon emissions from buildings in the park as the target, we used the fitting equation to solve for the remaining ΔDBH and infer the duration of tree growth required to achieve carbon neutrality, thereby predicting the timing of carbon neutrality. The specifications of trees and buildings in two virtual parks (A and B) are based on project data from parks in eastern and southern China and are applied in the validation of the prediction model. After data standardization, Parks A and B showed carbon sequestration capacities of 2,371.65 and 2,156.29 t, respectively, while their building carbon emissions reached 6,485.64 and 6,198.42 t, respectively. Current carbon sequestration only offsets approximately 35% of building carbon emissions in both parks. The results indicate that the predicted dates for both parks to achieve carbon neutrality (October 2038 and April 2035) are significantly later than the dates predicted directly based on linear carbon sequestration rates (April 2032 and May 2030), with error margins of 56.7% and 57.7%, respectively. Park A requires an additional 9.8 cm DBH growth per tree, while Park B needs 8.9 cm growth per tree. Economic analysis revealed that the total construction costs (seedlings + building materials) were 15.84 million and 20.26 million yuan for Parks A and B, respectively, with current ecological economic benefits of 3.46 million and 3.15 million yuan, indicating that ecological benefit balance points would be reached earlier than carbon neutrality timing. The study integrated the data processing and calculation workflow into a Python-based software tool, enabling automated analysis from engineering list import to result visualization. This paper emphasizes that achieving carbon neutrality solely through tree carbon sinks requires an extremely long time period, and the carbon neutrality duration can be significantly shortened by using local materials and zero-carbon building materials such as Cross Laminated Timber (CLT). When different proportions of conventional building materials are replaced with CLT, the carbon neutrality timeline can be substantially reduced, with complete replacement potentially achieving immediate carbon neutrality. This research provides a carbon neutrality prediction model and methodology for urban park development, which can be directly calculated based on the bill of quantities, significantly reducing workload and offering practical guidance for optimizing solutions for enterprises and decision-makers in low-carbon oriented park design and management.