Abstract: Propositional model counting or #SAT is the problem of computing the number of models for a given propositional formula. The rigorous theoretical analysis of algorithms for solving #SAT have been proposed in the literature. The time complexity is calculated based on the size of the #SAT instances, depending on not only the number of variables, but also the number of clauses. Researches on the worst case upper bound for #SAT with the number of clauses as the parameter can not only measure the efficiency of the algorithms, but also correctly reflect their performance. Therefore, it is significant to exploit the minimized upper bound of #SAT problem in the worst case using the number of clauses as the parameter. In this paper, we firstly analyze the CER algorithm which we have proposed for solving #SAT and prove an upper bound O(2\+m) regarding the number of clauses as the parameter. In order to increase the efficiency, an algorithm MCDP based on Davis-Putnam-Logemann-Loveland (DPLL) for solving #3-SAT is presented. By analyzing the algorithm, we obtain the worst-case upper bound O(1.8393\+m) for #3-SAT, where m is the number of clauses in a formula.