This article takes A-share manufacturing listed companies in the Shanghai and Shenzhen stock markets as the research subjects. Firstly

22 financial indicators were preliminarily determined based on the selection principles of warning indicators. Then

financial data of companies in financial crisis and normal companies in 2023 were obtained from the Guotai An database

and descriptive statistics were conducted using SPSS software. Subsequently

data from 135 financially distressed companies and 270 financially normal companies were extracted and subjected to significant difference testing using STATA software. Ultimately

19 financial indicators were determined

and two financial warning models were constructed. The following conclusions were drawn: (1) Manufacturing listed companies that have fallen into financial crisis difficulties have not been resolved

and the number of financially distressed companies each year remains basically unchanged. (2) Compared with financially normal companies

companies in financial crisis face greater debt repayment pressure

limited development space

weaker profitability

and lower operational efficiency; (3) The prediction performance of the neural network financial warning model and the multivariate discriminant financial warning model is good

with prediction accuracies of 86.8% and 84.8%

respectively

both reaching over 80%. Among them

the radial basis function neural network financial warning model has better predictive performance and can effectively control and prevent financial risks.