Trichloromethane (TCM) in soil causes adverse effects on the soil ecosystem and human health. Therefore, it is urgent to develop an efficient and low-cost soil TCM removal technology. In this study, we prepared sodium alginate-biochar-laccase immobilized pellets (SA-BC-LC) using composite immobilization technology, exploring the fitting impact of artificial neural network model (ANN) and general linear model (GLM) models on laccase loading and the correlation properties of SA-BC-LC. The SA-BC-LC exhibited a porous multi-layer network structure internally. Compared to free laccase, the relative activity of SA-BC-LC remained above 50 % after 5 reuses and still maintained at 48 % after 50 days of storage. Moreover, SA-BC-LC demonstrated significant capacity for adsorption and degradation of TCM in soil with ratios approximately at 31.3 % and 68.7 %, respectively. During the remediation process of TCM-contaminated soil from Taizhou Chemical plant, there was a rapid decrease in TCM concentration within the first hour. Under IM (Immobilization) treatment (added with 5 % SA-BC-LC), the removal rate of TCM reached up to 88.9 % in the first hour. The adsorption of TCM by SA-BC-LC was mainly chemical adsorption, which induced the improvement of the relative abundance of the co-metabolic dechlorinated microbial Pseudomonas. Our research presents a promising material for effectively remediating soils contaminated with chlorinated hydrocarbons (CHs), with excellent removal efficiency.