Children with autism need appropriate educational toys to assist rehabilitation training, so as to inhibit the development of autism. Toys and related treatments for children with autism can alleviate some of the deficits of children with autism. By using toys as stimuli and various sensations obtained by children with autism or toys as a result of reinforcement, the improvement of certain capabilities expected by related therapies can be achieved through the process of stimulation and reinforcement. However, in the process of pediatrics toy development, it is difficult for toy designers to assess whether the purpose of stimulation and reinforcement can be achieved. There are many factors that affect the design of rehabilitation toys. The industry has not formed a unified design evaluation standard, and the effects of product rehabilitation training are uneven. A method based on the radial basis function (RBF) neural network was proposed in this research to study the rehabilitation design and evaluation of rehabilitation toys for children with autism. Firstly, according to the three demand indicators for the evaluation of rehabilitation training for children with autism, that is, “useful, educational, and entertaining,” the analytic network process (ANP) method was chosen as the weighting method for determining each indicator in the overall evaluation. The RBF neural network rehabilitation model for children with autism was designed and evaluated. The maximum error of the model was less than 10%. The evaluation method was objective and reasonable, so as to provide a reference for the more accurate design evaluation, purchase, and development of rehabilitation toys for children with autism.