Abstract: The ecological stability of aquatic microecosystems in rice–crab co-culture systems is essential for regulating nutrient cycling, maintaining water quality, and sustaining the long-term functioning of integrated agricultural ecosystems. However, the mechanisms underlying bacterial community stability under seasonal environmental fluctuations and intensive aquaculture management remain poorly understood. This study investigated the temporal dynamics of bacterial community succession, assembly mechanisms, co-occurrence network characteristics, and environmental regulatory pathways throughout the rice–crab cultivation cycle. Water samples were collected at five key growth stages from April to August, and bacterial communities were characterized using 16S rRNA gene high-throughput sequencing. Multiple ecological approaches, including α and β diversity analyses, the neutral community model (NCM), modified stochasticity ratio (MST), PER-SIMPER, dispersal–niche continuum index (DNCI), co-occurrence network analysis, and structural equation modeling (SEM), were integrated to quantify bacterial community assembly and ecological stability. The results showed significant temporal variations in bacterial α and β diversity during the cultivation period (P < 0.05). Proteobacteria, Bacteroidota, and Actinobacteriota were the dominant phyla, collectively accounting for more than 60% of total bacterial abundance. Community dissimilarity was mainly driven by species turnover, which contributed more than 80% of β diversity in all sampling months, whereas nestedness accounted for only 3.3%–12.5%, indicating rapid bacterial species replacement under changing environmental conditions. NCM analysis revealed that bacterial communities generally followed neutral assembly patterns, with model explanatory power increasing from R² = 0.481 in April to R² = 0.678 in June, and the overall model explaining 65.1% of community variation (R² = 0.651). Meanwhile, MST values increased from 44.65% in April to 54.93%, 67.89%, 57.64%, and 64.29% from May to August, respectively, demonstrating a transition from deterministic environmental filtering during the early stage to stochastic processes dominating during the middle and late stages. PER-SIMPER and DNCI analyses further confirmed the increasing contribution of stochastic processes, particularly dispersal and ecological drift, to bacterial community assembly. Co-occurrence network analysis revealed pronounced temporal restructuring of microbial interactions. Network complexity and stability were relatively low during the early cultivation stage but increased substantially during the middle and late stages. In June, the bacterial network exhibited the strongest connectivity, with average degree, graph density, and average clustering coefficient reaching 29.817, 0.229, and 0.642, respectively, while average path length decreased to 2.315. Correspondingly, the comprehensive network complexity and stability indices increased from 5.02 and 16.67 in April to maximum values of 73.95 and 83.33 in June, indicating enhanced microbial interactions and improved ecological resilience. SEM further revealed the relationships among environmental factors, community assembly processes, and ecological stability. The model showed excellent fitting performance (X² = 9.586, P = 0.388, RMSEA = 0.000), with environmental variables and assembly processes jointly explaining 59.0% of bacterial network stability variation. Nitrite nitrogen and total nitrogen positively influenced network stability, with standardized path coefficients of 0.559 and 0.475, respectively, whereas orthophosphate phosphorus strongly inhibited stochastic assembly (λ = −0.869). In contrast, stochastic assembly positively promoted network stability (λ = 0.397), highlighting its role as an intrinsic ecological buffering mechanism. Overall, this study demonstrates that enhanced stochastic assembly processes, coordinated nitrogen–phosphorus regulation, and microbial network restructuring jointly maintain ecological stability in rice–crab co-culture aquatic ecosystems. These findings provide new insights into microbial resilience mechanisms and offer quantitative guidance for nutrient management, water-quality regulation, and sustainable aquaculture practices in arid and environmentally sensitive regions.