The invention provides a process industry soft measurement modeling method for cross-production-line transverse information fusion, and the method is based on an end-to-end neural network model which is formed by connecting a time sequencefeature extraction network in a self-encoder form and a regression network in a front-and-back manner. A two-stage soft measurement model training strategy of pre-training-time sequence feature information fusion training is provided, and a performance index soft measurement model is safely, effectively and accurately established on a process industrial production line with insufficient data accumulation by introducing data of the production line with rich data accumulation. Therefore, soft measurement is carried out on some performance indexes which are difficult to directly measure or high in measurement cost in the process industry, and reference and guidance are provided for monitoring, optimizing and controlling various parameters in the production process of the process industry.