SecEff-Pred is a web server that leverages an ESM-2-based predictor, enhanced by an innovative data simulation strategy and a multi-task learning framework, to accurately predict the secretion efficiency of signal peptides in Bacillus subtilis. The online service supports detecting up to 1000 sequences at a time, and users can also download a local version of the python script to run an unlimited number of sequences. Since the input of the model needs to be consistent with the sequence format during training, users are required to upload sequences in fasta format. Protein sequences should be not less than 45 amino acids.