diff --git a/src/turnbull.rs b/src/turnbull.rs
index 2b64ea5..f536f3b 100644
--- a/src/turnbull.rs
+++ b/src/turnbull.rs
@@ -311,7 +311,7 @@ fn fit_turnbull_estimator(data: &mut TurnbullData, progress_bar: ProgressBar, ma
 		// --------
 		// ICM step
 		
-		let (p_new, s_new, ll_model_new) = do_icm_step(data, &p, &s, ll_model_after_em);
+		let (p_new, s_new, ll_model_new) = do_icm_step(data, &p, &s, ll_tolerance, ll_model_after_em);
 		
 		let ll_change = ll_model_new - ll_model;
 		let converged = ll_change <= ll_tolerance;
@@ -400,7 +400,7 @@ fn do_em_step(data: &TurnbullData, p: &Vec<f64>, s: &Vec<f64>) -> Vec<f64> {
 	return p_new;
 }
 
-fn do_icm_step(data: &TurnbullData, _p: &Vec<f64>, s: &Vec<f64>, ll_model: f64) -> (Vec<f64>, Vec<f64>, f64) {
+fn do_icm_step(data: &TurnbullData, p: &Vec<f64>, s: &Vec<f64>, ll_tolerance: f64, ll_model: f64) -> (Vec<f64>, Vec<f64>, f64) {
 	// Compute Λ, the cumulative hazard
 	// Since Λ = -inf when survival is 1, and Λ = inf when survival is 0, these are omitted
 	// The entry at lambda[j] corresponds to the survival immediately before time point j + 1
@@ -477,6 +477,12 @@ fn do_icm_step(data: &TurnbullData, _p: &Vec<f64>, s: &Vec<f64>, ll_model: f64)
 			return (p_new, s_new, ll_model_new);
 		}
 		
+		if ll_model - ll_model_new < ll_tolerance {
+			// LL decreased but by less than ll_tolerance
+			// This might happen because the EM algorithm already obtained the exact solution
+			return (p.clone(), s.clone(), ll_model);
+		}
+		
 		step_size_exponent += 1;
 		
 		if step_size_exponent > 10 {